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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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    Evaluation of SERS activity for cosputtered Ag-ZnX@PS (X = O, S, Se) composites: Carrier density dependence

    Zhao, LinaChen, LeiJung, Young MeeTang, Chenghao...
    6页
    查看更多>>摘要：Ag-ZnX (X = O, S, Se) composites coated on polystyrene (PS) arrays (Ag-ZnO@PS, Ag-ZnS@PS, AgZnSe@PS) were successfully fabricated by using cosputtering technology. We found that ZnX doping decreased the carrier densities of these composites compared to that of pure Ag@PS, which was due to redistribution of electrons between Ag and ZnX. Thus, the carrier density of Ag was decreased, and the surface plasmon resonance (SPR) of Ag was redshifted in the Ag-ZnX composites. As the redshift of the SPR of Ag induced a high SPR contribution to the surface-enhanced Raman scattering (SERS), the SPR and charge transfer (CT) contributions were simultaneously increased with increasing carrier density in the Ag-ZnX composites. This study opens a new path to designing metal-semiconductor composites with controllable carrier density. Regulation of the carrier density will be of great help in understanding SPR and CT contributions. (c) 2022 Published by Elsevier B.V.
      原文链接:
    • NSTL
    • Elsevier

    Exploring the potential of UAV hyperspectral image for estimating soil salinity: Effects of optimal band combination algorithm and random forest

    Zhu, ChuanmeiDing, JianliZhang, ZipengWang, Zheng...
    8页
    查看更多>>摘要：Hyperspectral remote sensing by unmanned aerial vehicle (UAV) is an important technical tool for rapid, ac-curate, and real-time monitoring of soil salinity in arid zone agroecosystems. However, the key to effective soil salinity (electrical conductivity, EC) prediction by UAV visible and near-infrared (Vis-NIR) spectroscopy depends on the selection of effective features selection techniques and robust prediction characteristics algorithms. Therefore, in this study, two advanced feature selection methods and two commonly used modeling methods were applied to predict and characterize the spatial patterns of soil salinity (EC). The aim of this study was to explore the predictive performance of different feature band selection methods and to identify a robust soil salinity mapping strategy. The results demonstrated that standard normal variate (SNV) pre-processing broad-ened the absorption characteristics of the spectrum. Compared with competitive adaptive reweighted sampling (CARS), the optimal band combination algorithm (OBCA) strengthened the correlation with soil salinity and had a higher variable importance in the modeling. Random forest (RF) was more stable in mapping the spatial pattern of surface soil salinity compared to the partial least squares regression model (PLSR). Our results confirm the effectiveness of OBCA and RF in the developing UAV remote sensing models for surface soil salinity estimation and mapping.
      原文链接:
    • NSTL
    • Elsevier

    A comparative study of MIR and NIR spectral models using ball-milled and sieved soil for the prediction of a range soil physical and chemical parameters

    de Santana, Felipe BachionDaly, Karen
    15页
    查看更多>>摘要：This study evaluated the influence on predicted physical and chemical parameters of soil particle sizes commonly used in the infrared spectra acquisition, < 0.100 mm (ball-milled) and < 2 mm for MIR and NIR ranges, respectively. The influences were evaluated through the accuracy (RMSEP and RPIQ) results and the chemical information extracted by multivariate classification and regression models. For this a national population of soils containing 888 samples from 225 modal soil profiles, each with the reference values of sand, silt, clay, pH(CaCl2), pH(Water), total carbon, organic carbon (OC), cation exchange capacity, nitrogen, aluminium and bulk density, was used. Spectra were collected in MIR and NIR ranges using samples with both particle sizes. For each soil attribute, 29 random calibration and validation sets were generated and SVM, PLS and Cubist regression models were built. This same strategy was used to classify the soil samples according to their respective horizons (1 or 27) using SVM, PLS-DA and random forest algorithms. Results obtained by the randomised calibration and validation set did not present positive or negative bias on the RMSEP and RPIQ values based on soil particle sizes. In general, random variations of the RMSEP and RPIQ values were observed for all soil attributes. In addition, ball-milled and < 2 mm spectral models did not present large differences in both accuracy parameters simultaneously. The median Matthews correlation coefficient values calculated by the classification models showed minor variations of 2.61% and 0.65% for samples from both particle sizes in MIR and NIR ranges, respectively. The 'Variable Importance in Projection' or VIP scores, calculated by PLS and PLS-DA models, did not show any large variation in the chemical information extracted from MIR and NIR spectra for models built using samples from both particle sizes. The results from this study show that scanning ball-milled or < 2 mm sieved soil samples will result in spectra models in MIR and NIR ranges with the same accuracy and same chemical information. This suggests there is a big potential to eliminate the ball-milling sample step in soil laboratories that use MIR and NIR vibrational spectroscopy techniques to predict soil attributes, thereby reducing the time and costs associated with soil analysis.
      原文链接:
    • NSTL
    • Elsevier

    Synthesis and application of the fluorescent furan and imidazole probesfor selective in vivo and in vitro cancer cell imaging

    Naderi, Parisa MehdizadehZargoosh, KiomarsQandalee, MohammadFiruzi, Omidreza...
    11页
    查看更多>>摘要：Development of imaging probes for identification of tumors in the early stages of growth can significantly reduce the tumor-related health hazards and improve our capacity for treatment of cancer. In this work, three different furan and imidazole fluorescent derivatives abbreviated as Cyclo X, SAC and SNO are introduced for in vivo and in vitro imaging of cancer cells. The fluorescence quantum yield values were 0.226, 0.400 and 0.479 for Cyclo X, SAC and SNO, respectively. The excitation and emission wavelengths of maximum intensity were (360, 452), (350, 428) and (350, 432) nm for Cyclo X, SAC and SNO, respectively. The MTT reduction assay was used to estimate the cytotoxic activity of the proposed derivatives against HT-29 (cancer) and Vero (normal) cell lines. Cyclo X showed no cytotoxic effect, while SAC and SNO showed significantly higher cytotoxicity against the tested cell lines than cisplatin as a well-known anticancer drug. In vitro fluorescence microscopic images obtained using HT-29 cells showed that Cyclo X produced very bright images. The in vivo cancer cell imaging using 4T1 tumor-bearing mice revealed that Cyclo X is selectively accumulated in the tumor without distribution in the mice body organs. The spectral and structural stability, large Stokes shift, non-cytotoxicity and high level of selectivity for in vivo imaging are properties that make Cyclo X a suitable candidate to be used for long-term monitoring of cancer cells.
      原文链接:
    • NSTL
    • Elsevier

    Characterization of degradation behaviors of PLA biodegradable plastics by infrared spectroscopy

    Wang, FangNan, ZhuSun, XiaolinLiu, Chang...
    10页
    查看更多>>摘要：In this paper, the degradation behavior of two kinds of polylactic acid (PLA) biodegradable material products (pure PLA cup cover and modified PLA straw) was studied. It was found that under the composting environment specified in the International Standard, in the first 35 days, the degradation rate of the straw (with 50%-60% poly butylenes succinate (PBS)) was faster than that of the pure PLA cup cover, but in the later stage, the PLA cup cover exceeded the straw and disintegrated preferentially, and both could be degraded in about 70 days. After further analyzing the far-infrared (FIR, can also be called THz) and mid infrared (MIR) spectra of cup cover and straw, we observed that the material structure had not changed until disintegration, only the ester bond was hydrolyzed, the polymers became oligomers, which could be reflected in the change of the effective area of the characteristic peak at 7.15 THz (cup cover, labeled 1921) and 6.99 THz (straw, labeled 4386) in the THz spectrum. With the degradation, the effective area decreased continuously. Due to the strong absorption of the material in MIR band, most characteristic peaks were flattened and lost analytical value. The bivariate correlation of degradation time, biodegradation rate, total carbon dioxide release and the effective area of the characteristic peak at 7.15 THz (1921) and 6.99 THz (4386) in THz spectrum was analyzed by SPSS software. We discovered that the degradation time was significantly positively correlated with biodegradation rate and carbon dioxide release at the level of 0.01 and negatively correlated with the effective area of characteristic peak at the level of 0.05. The biodegradation rate was significantly negatively correlated with the effective area of characteristic peak at the level of 0.01. Taking the degradation time as the independent variable and the biodegradation rate, carbon dioxide release and effective area of characteristic peak as the dependent variables, we got that the THz spectrum could be used to describe the degradation behavior of PLA products as long as appropriate coefficient correction was made. In this way, we could separate from the laboratory environment, study the impact of environmental diversification on material degradation performance, and reduce the cost of material degradation performance identification. Using density functional theory (DFT), reduced density gradient (RDG) method and visualization software, the changes of weak interaction position and intensity in the molecule during the polymerization of lactic acid into PLA were further analyzed. We found that the vibration of ester bond corresponded to the characteristic peak with weak intensity in the spectrum, and the peak with large intensity mainly originated from the out-of-plane swing of O-H bond in the molecule.
      原文链接:
    • NSTL
    • Elsevier

    Spectral and theoretical study of SARS-CoV-2 ORF10 protein interaction with endogenous and exogenous macroheterocyclic compounds

    Gubarev, Yu. A.Koifman, O. I.Koifman, M. O.Malyasova, A. S....
    8页
    查看更多>>摘要：The coronavirus disease 2019 (COVID-19) caused by the SARS-CoV-2 coronavirus has spread rapidly around the world in a matter of weeks. Most of the current recommendations developed for the use of antivirals in COVID-19 were developed during the initial waves of the pandemic, when resources were limited and administrative or pragmatic criteria took precedence. The choice of drugs for the treatment of COVID-19 was carried out from drugs approved for medical use. COVID-19 is a serious public health problem and the search for drugs that can relieve the disease in infected patients at various stages is still necessary. Therefore, the search for effective drugs with inhibitory and/or virucidal activity is a paramount task. Accessory proteins of the virus play a significant role in the pathogenesis of the disease, as they modulate the host's immune response. This paper studied the interaction of one of the SARSCoV-2 accessory proteins ORF10 with macroheterocyclic compounds - protoporphyrin IX d.m.e., Fe(III) protoporphyrin d.m.e. and 5,10,15,20-tetrakis(30-pyridyl)chlorin tetraiodide, which are potential inhibitors and virucidal agents. The SARS-CoV-2 ORF10 protein shows the highest affinity for Chlorin, which binds hydrophobically to the alpha structured region of the protein. Protoporphyrin is able to form several complexes with ORF10 close in energy, with alpha-and beta-molecular recognition features, while Fe (III)protoporphyrin forms complexes with the orientation of the porphyrin macrocycle parallel to the ORF10 alpha-helix. Taking into account the nature of the interaction with ORF10, it has been suggested that Chlorin may have virucidal activity upon photoexposure. The SARS-CoV-2 ORF10 protein was expressed in Escherichia coli cells, macroheterocyclic compounds were synthesized, and the structure was confirmed. The interaction between macrocycles with ORF10 was studied by spectral methods. The results of in silico studies were confirmed by experimental data.(C) 2022 Elsevier B.V. All rights reserved.
      原文链接:
    • NSTL
    • Elsevier

    Classification of local diesel fuels and simultaneous prediction of their physicochemical parameters using FTIR-ATR data and chemometrics

    Dockery, Christopher R.Vandenbos, Deidre D.Msimanga, Huggins Z.
    11页
    查看更多>>摘要：Class identification and prediction of physicochemical variables of eight diesel fuel brands collected from several stations within the Atlanta metropolitan area in the State of Georgia were investigated using principal component analysis (PCA), partial least squares discriminant analysis (PLS2-DA), and partial least squares regression (PLSR) as modeling techniques. The fuels were from a common pipeline, therefore, assumed to have very similar characteristics. Ten FTIR-ATR spectra per fuel brand were collected over the 650 - 4000 cm-1 mid-infrared region, and the 80 x 3351 matrix was submitted to PCA to determine if there were any clusters. Following PCA, the 80 x 3351 matrix was split into a training matrix (56x3351) and a test matrix (24x3351). PLS2-DA models were built and evaluated for class identification using dummy variables (I,0) as input matrix. For physicochemical variable predictions, models were developed via PLSR using the FTIR-ATR spectra training matrix and physicochemical variables obtained from the Georgia Department of Agriculture Labs as input. Correlation coefficients of the eight fuels ranged from 0.9960 to 0.9998. PCA revealed all eight clusters of the diesel fuels, regardless of the tight correlation coefficients range. With a 1.0 +/- 0.1 cut-off for fuel identification, the PLS2-DA models showed 100% correct predictions for four or five fuel brands, and 75% correct prediction for all eight fuel brands. PLSR predicted 100% correct physicochemical variables, with a RMSEP range of 0.019 to 1.132 for all 80 variables targeted.
      原文链接:
    • NSTL
    • Elsevier

    An indanone-based fluorescent probe for detection and imaging of Cys/ Hcy in living cells

    Zhang, ShuweiLiao, WenyiWang, XuewenWang, Xinyao...
    7页
    查看更多>>摘要：Effective detection of Cys and Hcy plays an important role in the diagnosis of diseases. In this work, a novel indanone-based fluorescent probe INIAc-CN for sensitively and effectively detecting Cys and Hcy was developed. The probe exhibited weak fluorescence, but obvious fluorescent enhancement after reacted with Cys/Hcy. Moreover, the good anti-interference and low cytotoxicity of the probe made it successfully applied for monitoring Cys and Hcy of in living cells.CO 2022 Elsevier B.V. All rights reserved.
      原文链接:
    • NSTL
    • Elsevier

    Efficient classification of Escherichia coli and Shigella using FT-IR spectroscopy and multivariate analysis

    Shen, HaoYang, FanYan, JintaoYang, Shouning...
    6页
    查看更多>>摘要：Accurate and effective discrimination of E. coli and Shigella is an important clinical issue, and there are many limitations in traditional methods of analysis. FT-IR shows great potential in the classification of bacteria with high specificity and low cost. In this study, we evaluated the efficiency of this technique when combined with multivariate analysis for rapid classification of E. coli and Shigella, which is difficult using traditional analytical methods. Machine learning and statistical tools were employed in combination with FT-IR to classify 14 E. coli and 9 Shigella strains. The classification accuracies for select E. coli and Shigella strains from blood agar were 0.7826, 0.8696, and 0.9565 at the genus, species, and strain levels, respectively. In addition, we used the FT-IR data of select strains from three different culture media for cross-validation, yielding an accuracy of 0.3681 at the strain level. These results indicate that the bacterial culture conditions have a significant impact on the FT-IR patterns. Based on this, an improved strategy for training an ensemble classifier model considering bacterial culture factors was constructed, resulting in almost perfect separation with an accuracy of 0.9394 for strain-level classification. These results show the potential of FT-IR combined with multivariate analysis for more reliable bacterial classification. (C) 2022 Elsevier B.V. All rights reserved.
      原文链接:
    • NSTL
    • Elsevier

    Facilely self-assembled and dual-molecule calibration aptasensor based on SERS for ultra-sensitive detection of tetrodotoxin in pufferfish

    Yin, LijunFan, MinYou, RuiyunLu, Yudong...
    8页
    查看更多>>摘要：Tetrodotoxin (TTX) is one of the most lethal neurotoxins, so the reliable quantitative analysis of TTX is crucial for food and environmental safety monitoring. Herein, a novel dual-molecule calibration aptasensor was developed for detection of TTX based on Surface-enhanced Raman scattering (SERS). The adaptive surface has high affinity recognition sites for the target of interest, which ensures the high specificity and stability of the aptasensor. In addition, the uniquely labeled signal molecules located in the Raman silent region (1800-2400 cm(-1)) can avoid the interference of other exogenous biological signal molecules. Meanwhile, in quantitative analysis, the SERS signal generated by the reporter is calibrate in real time using the second-order peak of silicon molecule (Si). The detection linear range of the aptasensor was 0.0319 ng/mL-319.27 ng/mL, with a limit of detection (LOD) of 0.024 ng/mL and the excellent uniformity (RSD = 8.8%) for TTX detection. As a promising and versatile detection candidate, the ultra-sensitive quantitative detection aptasensor of TTX had important practical significance, which can offer more favorable persuasion for TTX analysis in real seafood samples. (C) 2022 Published by Elsevier B.V.
      原文链接:
    • NSTL
    • Elsevier