查看更多>>摘要：Hydrogen peroxide (H2O2) plays pivotal roles in various biological functions and pharmacological activities. High selectivity and sensitivity remain challenges for fluorescent probes to detection of H2O2 with a large stokes shift. Herein, a new "turn-on" fluorescent probe (DCM-C) was designed based on the mechanism of intramolecular charge transfer (ICT). In PBS buffer (10 mM, pH 7.4, with 20% DMSO, v/v), DCM-C exhibited high selectivity and sensitivity for H2O2 over other interfering analytes with a large stokes shift (187 nm), and the detection limit was as low as 35.5 nM. In addition, the probe was effective for detecting exogenous and endogenous H2O2 in living cells, and identifying stained in cytoplasm. Moreover, the probe has been used successfully for determining H2O2 in zebrafish by fluorescence imaging. (C) 2021 Elsevier B.V. All rights reserved.
Antina, Lubov A.Kalyagin, Alexander A.Ksenofontov, Alexander A.Pavelyev, Roman S....
11页
查看更多>>摘要：In this article, we present synthesis, spectral characteristics, and results of DFT calculations of new CH(R)bis(BODIPY) 1-3. They are characterized by the conformational mobility and sensitivity of fluorescence to polarity, proton-, electron donor ability and viscosity of the solvation environment. It is shown that fluorescence intensity of 1-3 increases in the homologous series of alcohols (ethanol, 1-propanol, 1-butanol, 1-octanol, 1-decanol) mainly due to decrease of medium acidic properties. The viscosity of the medium effects on the 1-3 fluorescence in a lesser degree. Compared to 1 and 2, the 3 is the most sensitive towards viscosity both in low-viscosity homologous alcohols and in high-viscosity ethanol-glycerol mixtures. In this regard, the sensitivity of fluorescence of CH(MeOPh)-bis(BODIPY) (compound 3) to the viscosity was studied in binary mixtures of polar DMF and low-polarity toluene with castor and vaseline oils, as well as to the macroviscosity of the solvate environment in mixtures of toluene with polystyrene. Prospects of the practical application of CH(R)-bis(BODIPY)s are proposed for the analysis of polarity, proton-donor properties and viscosity of the medium. (c) 2021 Elsevier B.V. All rights reserved.
Moroni, Aldana B.Vega, Daniel R.Kaufman, Teodoro S.Calvo, Natalia L....
10页
查看更多>>摘要：Albendazole is a benzimidazole-type active pharmaceutical ingredient, and one of the most effective broad-spectrum anthelminthic agents. The drug has two solid-state forms (ALB I and ALB II) which are desmotropes; both of them seem to be currently marketed. However, using the wrong crystalline solid form for formulation may have an undesired impact on the physicochemical and/or bioavailability prop-erties of the drug product. In order to develop new, simple, and less expensive alternatives toward the determination of the level of albendazole ALB I in its mixtures with ALB II, both desmotropes were prepared, and properly charac-terized by spectroscopic [solid-state nuclear magnetic resonance and near infrared (NIR)] and diffracto-metric (powder X-ray diffraction) methods. Then, the NIR and attenuated total reflectance-mid infrared (ATR-MIR) spectra of both forms were con-veniently pre-treated and employed for the development and optimization of partial least squares (PLS)-potentiated quantification models (NIR/PLS and ATR-MIR/PLS). The latter were also subjected to valida-tion (accuracy, precision, limits of detection and quantification, etc.) and further used to assess the level of the unwanted ALB II form in the bulk drug. The NIR/PLS method displayed the most satisfactory char-acteristics, including a limit of quantitation interval of 3.6 +/- 1 %w/w; it outperformed both, the ATR-MIR/ PLS counterpart (limit of quantitation interval of 14.0 +/- 3.4 %w/w) and a previously published and more demanding Raman/PLS alternative. (c) 2021 Elsevier B.V. All rights reserved.
查看更多>>摘要：Pesticide detection is of tremendous importance in agriculture, and Raman spectroscopy/SurfaceEnhanced Raman Scattering (SERS) has proven extremely effective as a stand-alone method to detect pesticide residues. Machine learning may be able to automate such detection, but conventional algorithms require a complete database of Raman spectra, which is not feasible. To bypass this problem, the present study describes a transfer learning method that improves the algorithm's accuracy and speed to extract features and classify Raman spectra. The transfer learning model described here was developed through the following steps: (1) the classification model was pre-trained using an open-source Raman spectroscopy database; (2) the feature extraction layer was saved after training; and (3) the training model for the Raman spectroscopy database was re-established while using self-tested pesticides and keeping the feature extraction layer unchanged. Three models were evaluated with or without transfer learning: CNN-1D, Resnet-1D, and Inception-1D, and they have improved the accuracy of spectrum classification by 6%, 2%, and 3%, with reduced training time and increased curve smoothness. These results suggest that transfer learning can improve the feature extraction capability and therefore accuracy of Raman spectroscopy models, expanding the range of Raman-based applications where transfer learning model can be used to identify the spectra of different substances. (c) 2021 Elsevier B.V. All rights reserved.
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