Spectrochimica acta. Part A, Molecular and biomolecular spectroscopy最新文献

In order to solve the problem of poor sensitivity and selectivity of conventional SERS substrates, we synthesized Mo_1-xW_xS₂@Ag₂S nanosheets in this paper by a two-step hydrothermal method. The structure and morphology of the synthesized Mo_1-xW_xS₂@Ag₂S nanosheets were characterized by XRD and SEM,respectively. The results show that the Mo_1-xW_xS₂@Ag₂S nanosheet has an irregular layered structure. Further, the SERS properties of Mo_1-xW_xS₂@Ag₂S nanosheets were tested by using rhodamine 6G (R6G), crystalline violet (CV), and 4-mercaptobenzoic acid (4-MBA) as probe molecules, respectively. The test results demonstrated that the nanosheets were specific to R6G and CV probe molecules, and the mechanism of selectivity was due to CT enhancement. In addition, Mo_1-xW_xS₂@Ag₂S exhibits ultrahigh sensitivity in R6G and CV, with the corresponding detection limit of both reached 10^-8 M. And linear fitting of the peak intensities was carried out, with the R² coefficient of 0.981 and 0.951, respectively. Finally, the relative standard deviations (RSDs) of this Mo1-xWxS2@Ag2S nanosheets was obtained to be 8.56 % by test 1 × 10^-4 M R6G at the characteristic peak 613 cm^-1, which represents excellent detection repeatability. The Mo_1-xW_xS₂@Ag₂S nanosheets are rich in edge-active sites favorable for charge transfer, which can enhance the SERS signals of the target molecules better. Besides, the Raman detection of the surface of Mo_1-xW_xS₂@Ag₂S nanosheets using nitrofurantoin (NFT) also reached a detection limit of 10^-8 M. Mo_1-xW_xS₂@Ag₂S nanosheets substrates can find applications in medicine and provide new strategies for improving the SERS performance.

Simple and eco-friendly biodegradable hydrotropes-assisted spectrophotometric experiments have been designed and validated to quantify ranolazine hydrochloride (RAN.HCl) in extended-release tablets. The citric acid and sodium citrate are employed as hydrotropes, serving as promising alternatives to polar organic solvents. The development of rapid and specific spectrophotometric experiments aimed at enhancing the spectral absorption of RAN.HCl. The spectrophotometric experiments are D⁰ and D^{0 AUC}, in which the highest peak absorbance was observed at 270.50 nm, with an AUC ranging from 265.00 to 275.50 nm. Moreover, spectral analysis of D¹ and D² were conducted with peak amplitudes recorded at 280.00 nm and 274.40 nm, respectively. The AUC in the wavelength ranges 275.00-287.00 nm for D¹, and 265.00-279.50 nm for D² were implemented to quantify RAN.HCl confirms no interference from the common additives incorporated into the marketed preparation. The optimized experiments disclosed a linear relationship in the 0.02-0.16 mg/mL concentration range. The accuracy was performed at 50-150 %, revealing an overall average recovery of 100.02 %. The lowest limits of RAN.HCl that could be accurately detected and quantified were 0.0016 and 0.0049, 0.0018 and 0.0055, 0.0058 and 0.0176, 0.0024 and 0.0075, 0.0074 and 0.0224, 0.0021 and 0.0064 mg/mL, respectively, across these investigations. Statistical analysis revealed no significant differences between the outcomes of the present investigation and those documented in literature reports, based on the t- and F-values at p = 0.05, which were below the theoretical values of 2.2622, 2.3646, 6.26, and 19.20, respectively.

The present work reports a sensitive, affordable, and ecologically friendly spectrofluorimetric method for the assessment of two antihypertensive medications, namely minoxidil and timolol. Blue-emitting sulfur and nitrogen co-doped carbon quantum dots (S,N-CQDs) were generated by exposing soluble starch and thiourea to a 15-minute microwave treatment. The so- prepared nanodots displayed fluorescence at 276/430 nm with a quantum yield of 22 %. Inspection of the so-prepared nano-sensor verified their doping with nitrogen and sulfur, and their size was in the range of 4.5-9.03 nm. The proposed method was found to be rectilinear in the range of 0.20-5.0 and 2.0-30.0 µg/mL, with LOQs of 0.16 and 0.82 µg/mL for minoxidil and timolol, respectively. The developed method was employed to assess the concentrations of minoxidil and timolol in their pharmaceutical formulations, with %recoveries varying between 99.00 % and 101.94 %, and low RSD values (less than 2 %). The high sensitivity of the developed method allowed its use for timolol measurement in artificial aqueous humor, with % recoveries between 97.60 %.and 101.57 %. The study further examined how each analyte interacted with the prepared dots, leading to a quenching of their fluorescence. Additionally, an interference study was utilized to evaluate the specificity of the proposed approach through determining analyte levels in the existence of common additives, co-formulated drugs, and co-administered drugs. The analytical eco-scale, GAPI and AGREE assessment techniques were utilized to confirm the suggested method greenness.

A novel colorimetric and fluorescent thiophenol probe based on dicyanoisophorone has been successfully achieved, which has low-cost, easy operation, high selectivity, sensitivity and stability. The chemosensor shows a large Stokes shift and approximately 170 nm when excited at 510 nm. ISO-DiNO₂ could be utilized as "Turn-on" and a naked-eyes chemosensor to detect PhSH, which is accompanied by a distinct color shift from red to dark purple with strong red fluorescence at 365 nm UV-light. Its limit of detection was determined to be 1.15 μM. More importantly, ISO-DiNO₂ can react instantaneously (<10 s) with PhS^-. In addition, ISO-DiNO₂ has been utilized in test paper strips, water sample together with imaging of PhS^- in living Raw264.7 cells, demonstrating that ISO-DiNO₂ has excellent and promising applications.

Herein, we report pyrene-tagged amide and urea-based sugar derivatives 1 and 2 in a simple synthetic pathway to recognize I^- and Hg²⁺ ions. Both molecules showed absorbance and fluorescence selectivity towards iodide ions in THF/H₂O (7/3, v/v) medium. The selectivity and sensitivity of 2 for iodide ions are superior to 1 due to more H-bond donors in 2. Interestingly, fluorometric receptor 2 exhibited aggregation-induced emission (AIE) at higher pH with a remarkable fluorometric color change. The AIE phenomenon might be explained by the self-association of 2 after forming imine functionality in the alkali medium. The Stern-Volmer plot showed the fluorescence quenching constant of each receptor with an iodide ion and indicated the quenching pathway. The LODs of 1 and 2 for iodide ions were evaluated as 0.84 and 0.17 µM, respectively. The 1:1 binding stoichiometry of 1 or 2 with iodide was found from the Job plot and verified by measuring the complex mass. Further, the complexes of each receptor with I^- ions can detect Hg²⁺ ions selectively by fluorescence turn-on method with low sensitivities (LODs: 0.008 µM for 1 and 0.01 µM for 2). DFT results were used to understand the binding mode of receptors 1 and 2 with iodide ions and the quenching process in the aqueous THF medium. The real application of the receptors was established for the recovery of iodide and Hg²⁺ ions from natural water samples.

It has been established that near infrared (NIR) spectroscopy has the potential of estimating sensory traits given the direct spectral responses that these properties have in the NIR region. In sweetpotato, sensory and texture traits are key for improving acceptability of the crop for food security and nutrition. Studies have statistically modelled the levels of NIR spectroscopy sensory characteristics using partial least squares (PLS) regression methods. To improve prediction accuracy, there are many advanced techniques, which could enhance modelling of fresh (wet and un-processed) samples or nonlinear dependence relationships. Performance of different quantitative prediction models for sensory traits developed using different machine learning methods were compared. Overall, results show that linear methods; linear support vector machine (L-SVM), principal component regression (PCR) and PLS exhibited higher mean R² values than other statistical methods. For all the 27 sensory traits, calibration models using L-SVM and PCR has slightly higher overall R² (x¯ = 0.33) compared to PLS (x¯ = 0.32) and radial-based SVM (NL-SVM; x¯= 0.30). The levels of orange color intensity were the best predicted by all the calibration models (R² = 0.87 - 0.89). The elastic net linear regression (ENR) and tree-based methods; extreme gradient boost (XGBoost) and random forest (RF) performed worse than would be expected but could possibly be improved with increased sample size. Lower average R² values were observed for calibration models of ENR (x¯ = 0.26), XGBoost (x¯ = 0.26) and RF (x¯ = 0.22). The overall RMSE in calibration models was lower in PCR models (X = 0.82) compared to L-SVM (x¯ = 0.86) and PLS (x¯ = 0.90). ENR, XGBoost and RF also had higher RMSE (x¯ = 0.90 - 0.92). Effective wavelengths selection using the interval partial least-squares regression (iPLS), improved the performance of the models but did not perform as good as the PLS. SNV pre-treatment was useful in improving model performance.

On the basis of first-principles electronic structure calculations, crystallographic parameters have been refined for calcium hydroxozincate (Qatranaite mineral), and the vibration properties (frequencies and eigenvectors) calculated. A detailed analysis of vibration modes is done, in the context of comparison with infrared and Raman spectra previously available. Special attention is paid to a posteriori symmetry analysis of vibration modes, discussing the latters' attribution to four irreducible representations of the P2₁/c space group, and to identifying stretchings and bendings of particular chemical bonds, pronounced in different vibrations. It turns out that high-frequency (>700 cm^-1) vibrations of hydroxyl groups bridging the Ca or Zn cations differ quite considerably for crystallographically distinct hydroxyl positions. It is shown that the vibrations involving hydroxyl groups and crystalline water typically come about in quadruplets at very close frequencies, whereby different irreducible representations reflect different combinations of similar "molecular" vibrations of four identical entities (of each hydroxyl or water) present in the unit cell. However, some vibrations show exceptions from this rule. In addition to interpretation of earlier experimental investigations, our study indicates that the low-frequency (<700 cm^-1) vibrations within the cation-hydroxyl connected skeleton are of more "solid-state-like" character and cannot be reasonably interpreted in terms of "molecular" vibrations within ZnO₄ or CaO₆ units.

Albumin is undoubtedly the most studied protein thanks to its widespread diffusion and biochemistry; despite its binding ability towards different dyes, provoking dye's colour change, has been exploited for decades for quantification purposes, the joint effect of working pH, ionic strength, and dye's pK_a still remains only sporadically discussed. In the present study, the interaction of Bovine Serum Albumin (BSA) with five dyes belonging to the sulfonephthalein group, Bromophenol Blue (BPB, pK_a = 3.75), Bromocresol Green (BCG, pK_a = 4.42), Chlorophenol Red (CPR, pK_a = 5.74), Bromocresol Purple (BCP, pK_a = 6.05) and Bromothymol Blue (BTB, pK_a = 6.72), is investigated at four working pH values (3.5, 6.0, 7.5 and 9.0) and two ionic strength conditions by UV-Vis spectroscopy. Principal Component Analysis is then applied to rationalize dye behavior upon BSA addition at each pH value and to summarize the protein effect on dyes' spectral features, identifying three general behaviors. The most relevant systems are then submitted to further characterization involving a solution equilibria study aimed at determining conditional binding constants for the selected DSA-dye adducts and fluorescence, CD, and ¹H NMR spectroscopy to evaluate the binding effect on the species involved.

Esophageal cancer is one of the leading causes of cancer-related deaths worldwide. The identification of residual tumor tissues in the surgical margin of esophageal cancer is essential for the treatment and prognosis of cancer patients. But the current diagnostic methods, either pathological frozen section or paraffin section examination, are laborious, time-consuming, and inconvenient. Raman spectroscopy is a label-free and non-invasive analytical technique that provides molecular information with high specificity. Here, we report the use of a portable Raman system and machine learning algorithms to achieve accurate diagnosis of esophageal tumor tissue in surgically resected specimens. We tested five machine learning-based classification methods, including k-Nearest Neighbors, Adaptive Boosting, Random Forest, Principal Component Analysis-Linear Discriminant Analysis, and Support Vector Machine (SVM). Among them, SVM shows the highest accuracy (88.61 %) in classifying the esophageal tumor and normal tissues. The portable Raman system demonstrates robust measurements with an acceptable focal plane shift of up to 3 mm, which enables large-area Raman mapping on resected tissues. Based on this, we finally achieve successful Raman visualization of tumor boundaries on surgical margin specimens, and the Raman measurement time is less than 5 min. This work provides a robust, convenient, accurate, and cost-effective tool for the diagnosis of esophageal cancer tumors, advancing toward Raman-based clinical intraoperative applications.

In this study, AgNPs-loaded polyurethane-sodium alginate (PU-S/Alg) composite polymers were prepared by precipitation polymerization and in-situ reduction method. Their catalytic potential was evaluated for the reduction of methyl orange (MO), brilliant blue (BB), Rhodamine B (RhB), 4-nitroaniline (4-NA), and 4-nitrophenol (4-NP). Successful preparation of samples was confirmed by UV-Visible spectrophotometry (UV-Visible), Fourier transform infrared (FTIR), and Scanning electron microscopy (SEM) analysis. During the catalytic study, the value of k_app for the reduction of MO in the presence of NaBH₄ and catalyst was found 0.488 min^-1 while, in the presence of NaBH₄ and catalyst alone, were found as 0.9 × 10^-4 and 0.8 × 10^-5 min^-1, respectively which indicates the role of catalyst in making the reaction speedy. The value of k_app for the reduction of BB, RhB, 4-NA, and 4-NP was found as 0.764, 0.475, 0.212 and 0.757 min^-1, respectively. Simultaneous reduction of dyes induced a decreased reaction completion time under the same reaction conditions. A slight increase in the value of k_app for the catalytic reduction of MO was also observed when reactions were performed in the presence of ionic media of different salts such as NaCl, KCl, CaCl_2, and MnCl₂. The rate of reduction of MO was increased with the increase in ionic strength of the medium. However, the presence of SDS (surfactant) in the reaction mixture induced the decreased activity of the catalyst and increased reaction completion time. The same value of k_app for the reduction of MO was observed in the case of freshly prepared and several days old nanocomposite catalyst. These results illustrate the stability and maintained catalytic potential of metal NPs for a prolonged time. Our reported catalyst also showed good potential for the treatment of dyes-polluted textile industry wastewater.