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Spectrochimica acta
Pergamon
Spectrochimica acta

Pergamon

1386-1425

Spectrochimica acta/Journal Spectrochimica acta
正式出版
收录年代

    Assessing the quality of stored red blood cells using handheld Spatially Offset Raman spectroscopy with multisource correlation analysis

    Vardaki, Martha Z.Schulze, H. GeorgSerrano, KatherineBlades, Michael W....
    10页
    查看更多>>摘要：In this work we employ Spatially Offset Raman Spectroscopy (SORS) to non-invasively identify storage-related changes in red blood cell concentrate (RCC) in-situ within standard plastic transfusion bags. To validate the measurements, we set up a parallel study comparing both bioanalytical data (obtained by blood-gas analysis, hematology analysis and spectrophotometric assays), and Raman spectrometry data from the same blood samples. We then employ Multisource Correlation Analysis (MuSCA) to correlate the different types of data in RCC. Our analysis confirmed a strong correlation of glucose, methemoglobin and oxyhemoglobin with their respective bioassay values in RCC units. Finally, by combining MuSCA with k- means clustering, we assessed changes in all Raman wavenumbers during cold storage in both RCC Raman data from the current study and parallel RCC supernatant Raman data previously acquired from the same units. Direct RCC quality monitoring during storage, would help to establish a basis for improved inventory management of blood products in blood banks and hospitals based on analytical data.(c) 2022 Elsevier B.V. All rights reserved.
      原文链接:
    • NSTL
    • Elsevier

    A novel hydrogen peroxide fluorescent probe for bioimaging detection and enables multiple redox cycles

    Ma, TaoFu, KaiLi, ZhichunYuan, Chuangchun...
    8页
    查看更多>>摘要：In this subject, a novel hydrogen peroxide (H2O2) fluorescent probe (MNG) was designed and developed using naphthalimide derivatives and selenomorpholine. In PBS buffer (10 mM, pH = 7.4, 1 %DMSO), the selenomorpholine on the probe is capable of qualitatively and quantitatively detecting (H2O2) at a small amount under a detection limit of 61 nM. The probe follows a mechanism that Se (II) in selenomorpholine is transformed to Se (IV), thus changing the spectra of the probe MNG. It is noteworthy that MNG can continuously make a cyclic response to H(2)O(2 )and glutathione (GSH), so it can potentially achieve redox process imaging in vivo. Moreover, this subject verified the redox process of the probe's continuous redox response in the Gaussian 09 programme through simulation calculation and mass spectrometry. The probe exhibits high biocompatibility. Moreover, it can detect H2O2 in MCF-7 cells and Argentine Bloodfin. (C) 2022 Elsevier B.V. All rights reserved.
      原文链接:
    • NSTL
    • Elsevier

    Reversible fluorescent test strip with red fluorescent carbon dots for monitoring water in organic solvents: Visual detection via a smartphone

    Ma, PinyiWu, QiongMu, XiaoweiSong, Xiaona...
    9页
    查看更多>>摘要：Herein, a novel type of red-emitting carbon dots called TN-CDs was created via a one-step hydrothermal approach using neutral red and tartaric acid as raw materials. The fluorescence of TN-CDs was gradually quenched as the amount of water increased, and the color of the solution changed from yellow to pink mauve (or purple to pink). The reaction could be completed within only 5 s in various organic solvents such as N,N-Dimethylformamide (DMF), methanol (MeOH), acetonitrile (ACN), and ethanol (EtOH) with linear detection ranges of 1.2%-35.0%, 0.5%-20.0%, 0.25%-5.0% and 0%-16.0%, respectively. In addition, we prepared a reusable test strip and then combined it with TN-CDs to detect water content in DMF, as well as integrated it with smartphone software, a UV lamp, and a dark chamber for real-time, on site, visual quantitative detection of the water content.(c) 2022 Elsevier B.V. All rights reserved.
      原文链接:
    • NSTL
    • Elsevier

    Blended fabric with integrated neural network based on attention mechanism qualitative identification method of near infrared spectroscopy

    Song, LimeiChen, EnzeZheng, TenglongLi, Jinyi...
    17页
    查看更多>>摘要：Near Infrared spectroscopy (NIRS) qualitative analysis technology has shown excellent development potential in the field of blend fabrics. However, the qualitative detection method based on the convolutional neural network (CNN) is difficult to accurately extract the feature of the spectral data, which will lead to missing detection or false detection; when using deep learning to build a qualitative detection model, due to interference of the external environment and other factors, the spectral data collected may have outliers, this means that the knowledge generalization on anomalous testing data, which may have a different distribution of that of the training set, is not trivial, which will also lead to missing detection or false detection. To solve the above problems, this paper proposes a novel qualitative detection neural network by analyzing the near infrared spectral data of blend fabrics. Firstly, we remove the convolutional layer and pooling layer of the CNN, making full use of the feature to enhance the feature representation ability of the model. Secondly, adding the L1 norm of the feature coefficients as a penalty term to the loss function to force those features with high redundancy to become weaker. Thirdly, in order to improve the recognition accuracy of the anomalous spectral data and minimize the model uncertainty, an ensemble machine learning approach utilizing 5 neural networks in parallel is used. To show the superiority of our proposed method, the existing methods are used as competitive methods to compare with our method. Our homemade dataset contains 3482 samples of blend fabrics with 9 different compositions. The results show that the Micro-F1-score, Micro-Specificity, Weight-F1-score, and Weight-Specificity of this method respectively 99.71%, 99.96%, 99.73%, and 99.99%, the results further confirm the method has higher analysis accuracy and stability. In addition, the method proposed in this paper can greatly improve the recognition accuracy of the anomalous spectral data. It has important practical value in the qualitative detection of blend fabrics.(c) 2022 Elsevier B.V. All rights reserved.
      原文链接:
    • NSTL
    • Elsevier

    A julolidine-chalcone-based fluorescent probe for detection of Al3+ in real water sample and cell imaging

    Li, PanpanLi, RunsenWang, KangnanLiu, Qiuxin...
    7页
    查看更多>>摘要：A fluorescent probe 1 based on julolidine-chalcone derivative, which can specifically recognize aluminum ion with high selectivity and anti-interference, was developed. Probe 1 has good fluorescence stability and can detect Al3+ with turn-on fluorescence in a wide pH range of 4.0-9.0. The probe has good repeatability for the detection of Al(3+ )and fluorescence turn-on and off can be repeated with the alternate Al(3+)and EDTA. The sensing mechanism is speculated that Al3+ will coordinate with hydroxyl oxygen and carbonyl oxygen on the probe through in situ 1H NMR and HRMS combing with Job's plot. The probe can also detect Al3+ in actual water samples and applied to monitor Al3+ in biological system. (C) 2022 Elsevier B.V. All rights reserved.
      原文链接:
    • NSTL
    • Elsevier

    Newly found K+-Thioflavin T competitive binding to DNA G-quadruplexes and the development of a label-free fluorescent biosensor with extra low detection limit for K+ determination in urine samples

    Chitbankluai, KhwanrudeeThavarungkul, PanoteKanatharana, ProespichayaKaewpet, Morakot...
    10页
    查看更多>>摘要：The determination of potassium ion K+ in body fluids is important in health monitoring and diagnoses. One of the interesting and simple methods for K+ detection is the use of label-free biosensors based on DNA G-quadruplexes (GQs) coupled with a specific fluorescent probe, such as Thioflavin T (ThT), which lights up when bound with K+-stabilized GQs. However, these biosensors are not generally sensitive. In this work, we found a solution: at a low concentration, K+ competes with ThT in binding to a bimolecular GQ or a tetramolecular GQ, resulting in a decrease in ThT fluorescence emission with increasing K+. Therefore, we developed a label-free turn-off fluorescent K+ sensor. The sensor provides a very low detection limit of 21.87 +/- 0.59 nM. Other possible interfering components in urine did not exert any effect even at quantities that were 10-fold greater than their upper limit of normal concentrations found in urine samples. With its only requirement of diluting samples, the developed low-cost label-free probe and simple sensor was successfully applied to the direct detection of K+ in normal urine samples with high accuracy (recoveries ranged from 90% to 100%).
      原文链接:
    • NSTL
    • Elsevier

    Rapid detection of hydrogen sulfide in vegetables and monosodium glutamate based on perylene supramolecular aggregates using an indicator displacement assays strategy

    Gao, XiaoLi, YiningZhang, JialinCheng, Nan...
    7页
    查看更多>>摘要：Hydrogen sulfide (H2S) has been clearly identified as a hazardous chemical pollutant that seriously affects food safety and human health. In order to develop a rapid, accurate and efficient H2S tracking method, this work propose a strategy based on indicator displacement assays (IDA). A water-soluble histidine-modified perylene diimide fluorescent probe was synthesized by a one-step method, and the probe can form supramolecular aggregates in the presence of Cd2+. There will be a fluorescence transformation of probe, caused by the change of the state of aggregation and adjusted by various concentration of S2-, which can achieve the fluorescence detection of S2-. The limit of detection is as low as 0.41 lmol/L. Particularly worth mentioning is that the probe in this work can be recycled for at least 5 times, which is environmentally friendly and economical. Finally, this method was applied in three kinds of vegetables and monosodium glutamate samples. (C)2022 Elsevier B.V. All rights reserved.
      原文链接:
    • NSTL
    • Elsevier

    A quantitative analysis method based on collision broadening for trace gas using terahertz heterodyne spectrometer

    Li, JiaDeng, XiaojiaoZheng, XiaopingLi, Li...
    8页
    查看更多>>摘要：Quantitative analysis of trace gases is an important research field in analytical chemistry. The terahertz electronic spectrometer is one of the most powerful tools for detecting trace gas. Here, a terahertz spectrometer based on frequency multiplier chain and heterodyne detection was presented. The rotational spectra of acetonitrile (CH3CN) gas were measured in the 290-370 GHz frequency band with 100 kHz spectral resolution. The spectrometer demonstrated excellent spectral specificity and the extrapolated limit of detection for CH3CN gas of 1.4 ppm. Furthermore, a novel quantification method of trace gas was proposed based on broadening mechanisms. The CH3CN self-and nitrogen (N-2)-collisional broadening coefficients were obtained experimentally for verifying the method. The CH3CN concentration of the validation group was calculated, and the relative error was 0.1%. The error analysis of the different number of measurements of the method was carried out. The method could provide a new perspective for trace gas quantitative analysis. (C)& nbsp;2022 Elsevier B.V. All rights reserved.
      原文链接:
    • NSTL
    • Elsevier

    A rapid fluorescence approach on differentiation of typical dinoflagellate of East China Sea

    Shan, ShihanXu, LeiChen, KeTong, Mengmeng...
    13页
    查看更多>>摘要：Detecting the marine phytoplankton by the means of absorption or fluorescence spectra were success-fully deployed in the past decades, however, the differentiation are mainly limited in levels of class, such as bacillariophytas, dinophytas, raphidophytes, chlorophytes, cyanobacteria, etc. which are characterized by their specific composition of photosynthetic pigments. To further differentiate the typical dinoflagel-late Prorocentrum donghaiense, Amphidinium carterae, Scrippsiella trochoidea, Karenia mikimotoi out of the common diatom Skeletonema costatum and haptonema Phaeocystis globosa at East China Sea, a rapid 3D-fluorescence method equipped with CHEMTAX model were conducted. Initial fluorescence excitation spectra of each algal species (under variable environmental conditions) were captured by 3D-fluorometer first. Then fingerprints of each algae were characterized by ten-point discrete excitation spectrum with the excitation wavelengths of 405, 420, 435, 470, 490, 505, 535, 555, 570 and 590 nm, which closely reflecting the difference of photosynthetic pigments. By equipping with CHEMTAX model, the standard spectra and norm spectra were constructed for FS-CHEMTAX (Fluorescence spectra-CHEMTAX) model to further identify the algal species and estimate the cell density. The developed method performed a bet-ter way of identifying the toxic species Amphidinium carterae, Phaeocystis globosa, and Karenia mikimotoi out of the non-toxic ones, with the identification accuracy rates of 83.3%, 90% and 100%, in monocultures, and 77.8%, 90% and 100%, in the bi-mixed cultures, respectively. Meanwhile, the detection limits for the three toxic species were found as low as 250, 1,400 and 120 cells/mL. The concentrations estimated are in good agreement with the microscopic cell counts for all the algae groups (correlation coefficients (R-2) exceed 0.8). The relative error of predict concentration was lowest for small cells, i.e., Phaeocystis globosa (10.0%) and Amphidinium carterae (21.1%), but the highest for big cells, i.e. Karenia mikimotoi (41.8%) when the target algae become the dominant species. The overall concentration detection error was no more than one order of magnitude, indicating that this method could provide an important technical support for monitoring the related harmful algal blooms. (C) 2022 Elsevier B.V. All rights reserved.
      原文链接:
    • NSTL
    • Elsevier

    Comprehensive examination and comparison of machine learning techniques for the quantitative determination of adulterants in honey using Fourier infrared spectroscopy with attenuated total reflectance accessory

    Dumancas, Gerard G.Ellis, Helena
    10页
    查看更多>>摘要：Facile, robust, and accurate analyses of honey adulterants are required in the honey industry to assess its purity for commercialization purposes. A stacked regression ensemble approach using Fourier transform infrared spectroscopic method was developed for the quantitative determination of corn, cane, beet, and rice syrup adulterants in honey. A training set (n=81) was used to predict the percent adulterant composition of the aforementioned constituents in an independent test set (n=32). A comprehensive comparison of the performance of various machine learning techniques including support vector regression using linear function, least absolute shrinkage and selection operator, ride regression, elastic net, partial least squares, random forests, recursive partitioning and regression trees, gradient boosting, and gaussian process regression was assessed. The predictive performance of the aforementioned machine learning approaches was then compared with stacked regression, an ensemble learning technique which collates the performance of the various abovementioned techniques. Results show that stacked regression did not primarily outperform other techniques across all four syrup adulterant constituents in the testing set data. Further, elastic net generalized linear model generated the optimum results (Root mean square error of prediction(RMSEP)average = 0.0107, R2average = 0.809) across all four honey adulterant constituents. Elastic net coupled with Fourier transform infrared spectroscopy may offer a novel, direct, and accurate method of simultaneously quantifying corn, cane, beet, and rice syrup adulterants in honey. (C) 2022 Elsevier B.V. All rights reserved.
      原文链接:
    • NSTL
    • Elsevier