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Spectrochimica acta
Pergamon
Spectrochimica acta

Pergamon

1386-1425

Spectrochimica acta/Journal Spectrochimica acta
正式出版
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    Development of silica molecularly imprinted polymer on carbon dots as a fluorescence probe for selective and sensitive determination of cetirizine in saliva and urine

    Cui, YixuanSu, AoxuanFeng, JingyingDong, Weichong...
    9页
    查看更多>>摘要：A fluorescence probe based on carbon dots (CDs) coated with silica molecularly imprinted polymer (MIPs) was synthesized for selective and sensitive determination of cetirizine (CTZ). Green source carbon dots were firstly derived from orange peels through a microwave method, and had the merits of eco-friendly and low toxicity. Then a thin silica film was formed on the surface of CDs by reverse microemul-sion technique, and molecularly imprinted polymer coated on silica-carbon dots. In this scene, CTZ, 3-aminopropyltriethoxysilane (APTES) and tetraethoxysilane (TEOS) were employed as a template, a func-tional monomer and cross linker, respectively. The obtained CDs-MIPs can selectively bind CTZ through the specific interaction between recognition sites and template, and obey photoinduced electron transfer fluorescence quenching mechanism. Fluorescence dropped linearly in the range of 0.5-500 ng mL-1, under the optimal conditions, with a detection limit of 0.41 ng mL-1. Furthermore, the proposed method was successfully intended for the determination of trace CTZ in human saliva and urine samples without the interference of other molecules and ions. And recoveries ranged from 95.8% to 99.8% with relative standard deviation less than 3.0%. (c) 2021 Elsevier B.V. All rights reserved.
      原文链接:
    • NSTL
    • Elsevier

    Photodynamics of biological active flavin in the presence of zwitterionic surfactants

    Jana, RabindranathGautam, Rajesh KumarBapli, AlokeSeth, Debabrata...
    10页
    查看更多>>摘要：In the flavin family of photoactive biomolecules, lumichrome (LM) is a very important compound. It contains a tri-cyclic structure with methyl groups at two sides. It formed by the partial decomposition and biodegradation of riboflavin in both acidic as well as in neutral medium. Herein, we have studied the photophysical properties of LM in the presence of two zwitterionic surfactants, namely dodecyldimethyl(3sulfopropyl) ammonium hydroxide inner salt (DSB), and tetradecyldimethyl(3-sulfopropyl) ammonium hydroxide inner salt (TSB), having the same head group but a different tail part. We have used steadystate absorption, fluorescence emission, and time-resolved fluorescence emission measurements. We observed that in the presence of zwitterionic surfactant aggregates LM shows excitation and emission wavelength dependent emission properties, which demonstrate the structural changes that take place from one form to another prototropic form of LM molecule. The higher rotational relaxation time of LM in the case of DSB compared to TSB demonstrated that LM is facing more rigid environment in DSB micelles compared to TSB micelles. (c) 2021 Elsevier B.V. All rights reserved.
      原文链接:
    • NSTL
    • Elsevier

    Rapid determination and origin identification of total polysaccharides contents in Schisandra chinensis by near-infrared spectroscopy

    Wu, LunGao, YueRen, Wen-chenSu, Yang...
    7页
    查看更多>>摘要：In this study, a classification model was established based on near-infrared spectroscopy and random for -est method to accurately distinguish three samples of Schisandra chinensis from different habitats. At the same time, the feasibility of fast and effective prediction of polysaccharide contents in Schisandra chinen-sis by near-infrared spectroscopy combined with chemometrics was evaluated. In this paper, phenol sul-furic acid method was used to determine the content of total polysaccharides in samples, and partial least squares regression algorithm was used to link the spectral information with the reference value. Different spectral pretreatment methods were used to optimize the model to improve its predictability and stabil -ity. The results showed that random forest could distinguish these samples accurately, with an accuracy of 97.47%. In the established prediction model, the RMSEC of the optimal model calibration set is 0.0012, and the coefficient of determination Ris 0.9976. The RMSEP of prediction set is 0.0024, the coefficient of determination Ris 0.9922, and the RPD is 11.36. In general, the method has good stability and applica-bility, which provides a new analytical method for the identification of Schisandra chinensis origin and quality evaluation. (c) 2021 Elsevier B.V. All rights reserved.
      原文链接:
    • NSTL
    • Elsevier

    Raman spectroscopy and machine learning for the classification of breast cancers

    Zhang, LihaoLi, ChengjianPeng, DiYi, Xiaofei...
    7页
    查看更多>>摘要：Breast cancer is a major health threat for women. The drug responses associated with different breast cancer subtypes have obvious effects on therapeutic outcomes; therefore, the accurate classification of breast cancer subtypes is critical. Breast cancer subtype classification has recently been examined using various methods, and Raman spectroscopy has emerged as an effective technique that can be used for noninvasive breast cancer analysis. However, the accurate and rapid classification of breast cancer subtypes currently requires a great deal of effort and experience with the processing and analysis of Raman spectra data. Here, we adopted Raman spectroscopy and machine learning techniques to simplify and accelerate the process used to distinguish normal from breast cancer cells and classify breast cancer subtypes. Raman spectra were obtained from cultured breast cancer cell lines, and the data were analyzed by two machine learning algorithms: principal component analysis (PCA)-discriminant function analysis (DFA) and PCA-support vector machine (SVM). The accuracies with which these two algorithms were able to distinguish normal breast cells from breast cancer cells were both greater than 97%, and the accuracies of breast cancer subtype classification for both algorithms were both greater than 92%. Moreover, our results showed evidence to support the use of characteristic Raman spectral features as cancer cell biomarkers, such as the intensity of intrinsic Raman bands, which increased in cancer cells. Raman spec-troscopy combined with machine learning techniques provides a rapid method for breast cancer analysis able to reveal differences in intracellular compositions and molecular structures among subtypes. (c) 2021 Elsevier B.V. All rights reserved.
      原文链接:
    • NSTL
    • Elsevier

    Analysis of the ternary antiretroviral therapy dolutegravir, lamivudine and abacavir using UV spectrophotometry and chemometric tools

    Serag, AhmedHasan, A. MohamedTolba, H. EnasAbdelzaher, M. Ahmed...
    7页
    查看更多>>摘要：Herein, a simple spectrophotometric method coupled with chemometric techniques i.e. partial least square (PLS) and genetic algorithm (GA) were utilized for the simultaneous determination of the vital ternary antiretroviral therapy dolutegravir (DTG), lamivudine (LMV), and abacavir (ACV) in their com-bined dosage form. Calibration (25 samples) and validation (13 samples) sets were prepared for these drugs at different concentrations via implementing partial factorial experimental designs. The zero order UV spectra of calibration and validation sets were measured and then subjected for further chemometric analysis. Partial least squares with/without variable selection procedures i.e. genetic algorithm (GA) were utilized to untangle the UV spectral overlapping of these mixtures. Cross-validation and external valida-tion methods were applied to compare the performance of these chemometric techniques in terms of accuracy and predictive abilities. It was found that six latent variables were optimum for modelling DTG, four latent variables for modelling LMV and three latent variables for modelling ACV. Although, good recoveries with prompt predictive ability were attained by these PLS, GA-PLS showed better analyt-ical performance owing to its capability to remove redundant variables i.e. the number of absorbance variables have been reduced to about 21-29%. The proposed chemometric methods can be reliably applied for simultaneous determination of DTG, LMV, and ACV in their laboratory prepared mixtures and pharmaceutical preparation posing these chemometric methods as worthy and substantial analytical tools in in-process testing and quality control analysis of many antiretroviral pharmaceutical preparations. (c) 2021 Elsevier B.V. All rights reserved.
      原文链接:
    • NSTL
    • Elsevier

    An online, non-destructive method for simultaneously detecting chemical, biological, and physical properties of herbal injections using hyperspectral imaging with artificial intelligence

    Zhong, YiRu, ChenleiWang, ShufangLi, Zhenhao...
    11页
    查看更多>>摘要：Botanical drugs hold great potential to prevent and treat complex diseases. Quality control is essential in ensuring the safety, efficacy, and therapeutic consistency of these drug products. The quality of a botanical drug product can be assessed using a variety of analytical methods based on criteria that judge the identity, strength, purity, and potency. However, most of these methods are developed on separate analytical platforms, and few approaches are available for in-process monitoring of multiple quality properties in a non-destructive manner. Here, we present a hyperspectral imaging-based strategy for online measurement of physical, chemical, and biological properties of botanical drugs using artificial intelligence algorithms. An end-to-end convolutional neural network (CNN) model was established to accurately determine phytochemicals and bioactivities based on the spectra. Besides, a new dual-scale anomaly (DSA) detection algorithm was proposed for visible particle inspection based on the images. The strategy was exemplified on Shuxuening Injection, a Ginkgo biloba-derived drug used in the treatment of cerebrovascular and cardiovascular diseases. Four quality metrics of the injection, including total flavonol, total ginkgolides, antioxidant activity, and anticoagulant activity, were successfully predicted by the CNN model with validation R2 of 0.922, 0.921, 0.880, and 0.913 respectively, showing better performance than the other models. Unqualified samples with visible particles could be detected by DSA with a low false alarm rate of 9.38 %. Chromaticity results indicated that the inter-company variations of color were significant, while intra-company variations were relatively small. This demonstrates a real application of integrating hyperspectral imaging with artificial intelligence to provide a rapid, accurate, and non-destructive approach for process analysis of botanical drugs. (c) 2021 Elsevier B.V. All rights reserved.
      原文链接:
    • NSTL
    • Elsevier

    Near-infrared spectra of liquid and gas samples by diffuse reflectance employing benchtop and handheld spectrophotometers

    Paiva, Eduardo MaiaRibessi, Rafael LuisRohwedder, Jarbas Jose Rodrigues
    8页
    查看更多>>摘要：This paper describes a new method to obtain NIR spectra of liquid and gas samples by diffuse reflectance, which is especially suitable for handheld spectrophotometers, since most of these instruments are designed to acquire spectrum using this geometry. The core of the method is a diffuse reflectance cell, which consists of a vial containing a mixture of the liquid or gas sample (rare medium) and a powder (dense medium). Using this strategy, no adaptation is required to measure spectra with most portable NIR spectrometers. This new method was used to obtain NIR spectra of several liquids and gases, which were compared with traditional transmittance spectra. As a proof of concept, measurements of biodiesel/ vegetable oil/diesel blends were used to build multivariate calibrations to predict the contents of biodiesel and vegetable oil in diesel blends using benchtop and handheld FT-NIR spectrophotometers. This lowcost method was demonstrated to be suitable for overcoming problems related to the handling of viscous samples and expand the applications with portable NIR instruments. (c) 2021 Elsevier B.V. All rights reserved.
      原文链接:
    • NSTL
    • Elsevier

    Interaction of graphene oxide with lysozyme:Insights from conformational structure and surface charge investigations

    Li, BinbinHao, ChangchunLiu, HengyuYang, Haiyan...
    13页
    查看更多>>摘要：Lysozyme (Lyz) is an important antibacterial protein that exists widely in nature. In recent years, the application of graphene oxide (GO) in the field of biotechnology electronics, optics, chemistry and energy storage has been extensively studied. However, due to the unique properties of GO, the mechanism of its interaction with biomacromolecule proteins is very complex. To further explore the interaction between GO and proteins we explore the influence of different pH and heat treatment conditions on the interaction between GO and Lyz, the GO (0-20 mu g/mL) was added at a fixed Lyz concentration (0.143 mg/mL) under different pHs. The structure and surface charge changes of Lyz were measured by spectroscopic analysis and zeta potential. The results showed that the interaction between GO and Lyz depends on temperature and pH, significant changes have taken place in its tertiary and secondary structures. By analyzing the UV absorption spectrum, it was found that lysozyme and GO formed a stable complex, and the conformation of the enzyme was changed. In acidic pH conditions (i.e., pH < pI), a high density of Lyz were found to adsorb on the GO surface, whereas an increase in pH resulted in a progressive decrease in the density of the adsorbed Lyz. This pH-dependent adsorption is ascribed to the electrostatic interactions between the negatively charged GO surface and the tunable ionization of the Lyz molecules. The secondary structure of Lyz adsorbed on GO was also found to be highly dependent on the pH. In this paper, we investigated the exact mechanism of pH-influenced GO binding to lysozyme, which has important guidance significance for the potential toxicity of GO biology and its applications in biomedical fields such as structure-based drug design. (C) 2021 Elsevier B.V. All rights reserved.
      原文链接:
    • NSTL
    • Elsevier

    A new method for predicting the acute toxicity of carbamate pesticides based on the perspective of binding information with carrier protein

    Xing, YueWang, ZishiLi, XiangshuaiHou, Chenxin...
    13页
    查看更多>>摘要：Toxicity is one of the most important factors limiting the success of new drug development. In this paper, we built a fast and convenient new method (Carrier protein binding information-toxicity relationship, CPBITR) for predicting drug acute toxicity based on the perspective of binding information with carrier protein. First, we studied the binding information between carbamate pesticides and human serum albumin (HSA) through various spectroscopic methods and molecular docking. Then a total of 16 models were established to clarify the relationship between binding information with HSA and drug toxicity. The results showed that the binding information was related to toxicity. Finally we obtained the effective toxicity prediction model for carbamate pesticides. And the "Platform for Predicting Drug Toxicity Based on the Information of Binding with Carrier Protein" was established with the Back-propagation neural network model. We proposed and proved that it was feasible to predict drug toxicity from this new perspective: binding with carrier protein. According to this new perspective, toxicity prediction model of other drugs can also be established. This new method has the advantages of convenience and fast, and can be used to screen out low-toxic drugs quickly in the early stage. It is helpful for drug research and development. (c) 2021 Elsevier B.V. All rights reserved.
      原文链接:
    • NSTL
    • Elsevier

    Determination of the denaturation temperature of the Spike protein S1 of SARS-CoV-2 (2019 nCoV) by Raman spectroscopy

    Hernandez-Arteaga, A. C.Ojeda-Galvan, H. J.Rodriguez-Aranda, M. C.Toro-Vazquez, J. F....
    9页
    查看更多>>摘要：In the present work the temperature response of the constitutive S1 segment of the SARS-CoV-2 Spike Glycoprotein (GPS) has been studied. The intensity of the Raman bands remained almost constant before reaching a temperature of 133 degrees C. At this temperature a significant reduction of peak intensities was observed. Above 144 degrees C the spectra ceased to show any recognizable feature as that of the GPS S1, indicating that it had transformed after the denaturation process that it was subjected. The GPS S1 change is irreversible. Hence, Raman Spectroscopy (RS) provides a precision method to determine the denaturation temperature (T-D) of dry powder GPS S1. The ability of RS was calibrated through the reproduction of T-D of other well studied proteins as well as those of the decomposition temperature of some amino acids (AA). Through this study we established a T-D of 139 +/- 3 degrees C for powder GPS S1 of SARS-CoV-2. (C) 2021 Elsevier B.V. All rights reserved.
      原文链接:
    • NSTL
    • Elsevier