查看更多>>摘要：In this paper, a one-dimensional shallow convolutional neural network structure combined with elastic nets (1D-SCNN-EN) was firstly proposed to predict the glucose concentration of blood by Raman spectroscopy. A total of 106 different blood glucose spectra were obtained by Fourier transform (FT) Raman spectroscopy. The one-dimensional shallow convolutional neural network, with elastic nets added to the full connected layer, was presented to capture multiple deep features and reduce the complexity of the model. The 1D-SCNN-EN model has a better performance than conventional approaches (partial least squares and support vector machine). The root mean squared error of calibration (RMSEC), the root mean squared error of prediction (RMSEP), the determination coefficient of prediction (R-P(2)), and the residual predictive deviation of prediction (RPD) were 0.10262, 0.11210, 0.99403, and 12.94601, respectively. The experiment results showed that the 1D-SCNN-EN model has a higher prediction accuracy and stronger robustness than the other regression models. The overall studies indicated that the 1D-SCNN-EN model looked promising for predict the glucose concentration of blood by Raman spectroscopy when the sample size is small. (C) 2021 Published by Elsevier B.V.
查看更多>>摘要：This study highlights the potential of surface-enhanced Raman scattering (SERS) to differentiate between B-cell lymphoma (BCL), T-cell lymphoma (TCL), lymph node metastasis of melanoma (Met) and control (Ctr) samples based on the specific SERS signal of DNA extracted from lymph node tissue biopsy. Differences in the methylation profiles as well as the specific interaction of malignant and nonmalignant DNA with the metal nanostructure are captured in specific variations of the band at 1005 cm-1, attributed to 5-methylcytosine and the band at 730 cm-1, attributed to adenine. Thus, using the area ratio of these two SERS marker bands as input for univariate classification, an area under the curve (AUC) of 0.70 was achieved in differentiating between malignant and non-malignant DNA. In addition, DNA from the BCL and TCL groups exhibited differences in the area of the SERS band at 730 cm-1, yielding an AUC of 0.84 in differentiating between these two lymphadenopathies. Lastly, using multivari-ate data analysis techniques, an overall accuracy of 94.7% was achieved in the differential diagnosis between the BCL, TCL, Met and Ctr groups. These results pave the way towards the implementation of SERS as a novel tool in the clinical setting for improving the diagnosis of malignant lymphadenopathy. (c) 2021 Elsevier B.V. All rights reserved.
查看更多>>摘要：Pregnancy diagnosis is essential for rabbit's reproductive management. The early identification of nonpregnant rabbits allows for earlier re-insemination, increases the service rate, and reduces the laboring interval in commercial operations. The objective of this study was to establish the feasibility of using a Vis-NIR spatially resolved spectroscopy for diagnosing pregnancy in female rabbits. A total of 141 female rabbits, including 67 pregnant female rabbits (PRs) and 74 non-pregnant female rabbits (NPRs), were measured spectrally between 350 and 1000 nm with different source-detector distances (SDD). Different preprocessing methods were used to transform and enhance the spectral signal. A partial least squares-discriminant analysis (PLS-DA) classification model of the original and preprocessed spectra was established. The highest accuracy of the calibration set and prediction set was 91.75% and 86.05%, respectively. Competitive adaptive reweighted sampling (CARS) and successive projection algorithm (SPA) were used to select characteristic wavelengths from the variables of VIP > 1 (Variable importance in projection),and four classification models were established based on selected wavelengths, including PLS-DA, support vector machine (SVM), K-Nearest Neighbor (KNN) and Naive Bayes. SPA-SVM was the optimal classification model, the sensitivity, specificity, and accuracy of the validation set and prediction set were 93.18%, 94.44%, 93.88%, 86.96%, 90.00%, 90.69% respectively. The results showed that Vis-NIR spatially resolved spectroscopy combined with classification models could discriminate the PRs and NPRs. (c) 2021 Published by Elsevier B.V.
查看更多>>摘要：In this paper, a fast and efficient analytical strategy was proposed that chemometrics assisted with excitation-emission fluorescence matrices was used to quantify carbaryl (CAR) and thiabendazole (TBZ) in peach, soil and sewage. Even if there are serious overlapped peaks and unknown interferences in fluorescence analysis, the second-order calibration method based on alternating trilinear decomposition (ATLD) algorithm can be used to analyze CAR and TBZ in peach, soil and sewage. The recoveries of CAR and TBZ in peach are 110.4% and 99.7% and their standard deviations are lower than 2.1% and 0.3%, respectively. In addition, the accuracy of the method was assessed with figures of merit as well as intra-day and inter-day precision. The limit of detection, the limit of quantitation of CAR and TBZ in peach are 1.2 ng mL(-1) and 0.3 ng mL(-1) , 3.5 ng mL(-1) and 0.8 ng mL(-1), respectively. And their rootmean-square error of prediction are 17.0 ng mL(-1) and 5.0 ng mL(-1) and there are high sensitivity and selectivity in this method. Meanwhile, the results obtained by ATLD algorithm were compared with those obtained by the self-weighted alternate trilinear decomposition algorithm (SWATLD) and the parallel factor analysis (PARAFAC) algorithm, and statistical methods such as the t-test, F-test and the elliptic joint confidence region were used to evaluate for analysis. There were no significant differences among these methods. At last, high performance liquid chromatography-fluorescence detector (HPLC-FLD) was used to evaluate the accuracy and reliability of the proposed method. These results are satisfactory and indicate that the proposed method can be used for accurate and rapid determination of pesticides in complex systems. (C) 2021 Elsevier B.V. All rights reserved.
查看更多>>摘要：Gastrodia elata is an obligate fungal symbiont used in traditional Chinese medicine. There are currently 4 grades of the plant based on the "Commodity Specification Standard of 76 Kinds of Medicinal Materials". The traditional discrimination methods for determining the medicinal grade of G. elata powders are complex and time-consuming which are not suitable for rapid analysis. We developed a rapid analysis method for this plant using attenuated total reflection and Fourier-transform infrared spectroscopy (ATR-FTIR) together with machine learning algorithms. The original spectroscopic data was first pretreated using the multiplicative scatter correction (MSC) method and 4 principal components were extracted using extremely randomized trees (Extra-trees) and principal component analysis (PCA) algorithms, and different kinds of classification models were established. We found that multilayer perceptron classifier (MLPC) modeling was superior to support vector machine (SVM) and resulted in validation and prediction accuracies of 99.17% and 100%, respectively and a modeling time of 2.48 s. The methods established from the current study can rapidly and effectively distinguish the 4 different types of G. elata powders and thus provides a platform for rapid quality inspection. (c) 2021 Elsevier B.V. All rights reserved.
查看更多>>摘要：Zn1-xMnxAl2O4:0.1 mol% Cr3+ (0.04 <= x <= 0.16) phosphors with single spinel phase were synthesized by using sol-gel method and the structure, optical and temperature sensing performances were reported herein. The results of X-ray photoelectron spectra indicate that the inversion defects related to octahedral Zn are reduced and the crystal field surrounding Al changes with Mn2+ doping in ZnAl2O4 lattices. Mn2+/Cr3+ co-doped ZnAl2O4 nanophosphors reveal a green emission band assigned to Mn2+ and a series of red emission peaks assigned to Cr-3+,Cr- respectively. With the concentration of Mn2+ increasing, the intensity of zero phonon line (R line) assigned to Cr3+ increases, reaching the maximum at the optimal Mn2+ concentration of x = 0.14. The energy transfer from Mn2+ to Cr3+ is confirmed with the energy transfer efficiency of 83%. The separation between E-2(e(g)) and E-2(t(g)) of Cr3+ is enlarged due to Mn2+ dopants giving rise to a change of crystal field. The luminous intensity ratio between two separated emission peaks at 685 nm (R-3) and 689 nm (R-2) reveals an obvious temperature dependence. The relative sensitivity changes from 3.7 %K-1 to 0.25 %K-1 with the temperature increasing from 80 K to 310 K, which is much larger than that of ZnAl2O4:Cr3+ nanophosphors wi(t)hout Mn2+, indicating its good application prospect in optical thermometry. (C) 2021 Elsevier B.V. All rights reserved.
查看更多>>摘要：Importance: One of the consequential and alarming complications of diabetes mellitus is diabetic neuropathy (DN). DN is assured to be caused chiefly by excess sorbitol levels in the body. The harmful consequences of DN alike peripheral nerve damage with extremity ulcers may be dodged with timely detection and treatment. The therapeutic methods for DN are scarce and expensive. Therefore economic and user friendly methodologies to prevent acquiring the disease need proper attention. Objective: The present research has been conducted (1) to analyse the levels of sorbitol in diabetic blood samples and compare them with non-diabetic ones and (2) to study the reduction in sorbitol levels upon addition of an important biochemical compounds caffeine in both sample groups. Research design, setting, participants and method: Sorbitol-caffeine interaction analysis of blood samples of 16 patients with type 2 diabetes from KPC Medical College, Kolkata, India was made. The spectroscopic analysis and their interpretations were compared with 16 healthy subjects. Main outcomes and measures: Present work describes that caffeine can be helpful in reducing the sorbitol level in diabetics, so the chances of development and progression of diabetic neuropathy can be controlled with the introduction of caffeine. Results: A total number of 32 blood samples of patients (aged 35-70 years); mean age ranges were 52.06 +/- 2.68 and 53.50 +/- 2.66 years for non-diabetic and diabetic ones respectively, glucose and sorbitol screening examination were done by enzymatic methodologies where concentrations were assessed by means of either absorption or fluorescence spectroscopy. The calibration range was 18.2-1119.3 mg/dL (Linear regression analysis r(2) = 0.996). The sensitivity of this screening program in detecting DN with the healthy adults has been inquired and found efficient. Results of fasting insulin analyses have also been analysed for HOMA-IR (homeostasis model assessment - insulin resistance) and HOMA-B (homeostasis model assessment - pancreatic beta cell function) values. Statistical significance of the results in non-diabetic and diabetic groups were performed and found to be statistically significant. Conclusions: We have defined the relationship between blood glucose level, insulin level, sorbitol and caffeine in human body and utilized them in the plausible remediation of DN. (C) 2021 Elsevier B.V. All rights reserved.
查看更多>>摘要：The inhibitory effects of engeletin on the activities of human cytochrome P450 3A4 and 2D6 (CYP3A4 and CYP2D6) were investigated by enzyme kinetics, multi-spectroscopy and molecular docking. Engeletin was found to strongly inhibit CYP3A4 and CYP2D6, with the IC50 of 1.32 lM and 2.87 lM, respectively. The inhibition modes of engeletin against CYP3A4 and CYP2D6 were a competitive type and a mixed type, respectively. The fluorescence of the two CYPs was quenched statically by engeletin, which was bound to CYP3A4 stronger than to CYP2D6 at the same temperature. Circular dichroism spectroscopy, three-dimensional fluorescence, ultraviolet-visible spectroscopy and synchronous fluorescence confirmed that the conformation and micro-environment of the two CYPs protein were changed after binding with enge-letin. Molecular docking, ultraviolet-visible spectroscopy and the fluorescence data revealed that enge-letin had strong binding affinity to the two CYPs through hydrogen and van der Waals forces. The findings here suggested that engeletin may cause the herb-drug interactions for its inhibition of CYP3A4 and CYP2D6 activities. (c) 2021 Elsevier B.V. All rights reserved.
查看更多>>摘要：Bovine serum albumin (BSA) has been used as a transporter protein for levothyroxine (LT4) and rutin, due to its property of binding to various ligands. Rutin binding to the BSA-LT4 complex can bring many benefits due to its proven pharmacological properties. Using Fourier-Transform Infrared Spectroscopy (FT-IR) the changes induced by rutin in the structure of BSA-LT4 complex were determined. Fluorescence studies allowed us to determine the quenching mechanism and affinity of rutin to the BSA-LT4 complex. The thermodynamic parameters suggest the binding of rutin to BSA-LT4 is a spontaneous process, driven by enthalpy and electrostatic forces. Also, the second derivative of the emission spectra suggests the Trp's of BSA are located in two different microenvironments. Thermal and chemical denaturation of BSA-LT4-rutin complex presents similar behavior but with better stability of the complex in case of chemical denaturation. Molecular docking studies show the binding of the two ligands to the same BSA site, suggesting that rutin may influence the bond of LT4 with the protein. Studies on the antioxidant activity of the BSA-LT4-rutin complex suggest that the presence of LT4 decreases the antioxidant activity of the rutin, but even so this antioxidant activity can be used to bring benefits for medical purposes. (c) 2021 Elsevier B.V. All rights reserved.
查看更多>>摘要：Surface plasmon resonance (SPR) generated in gold nanoparticles can induce the conversion of p-Aminothiophenol (PATP) molecules into p,p'-dimercaptoazobenzene (DMAB) molecules by coupling reaction under the action of excitation light. Molecular detection of samples by surface enhanced Raman spectroscopy (SERS) techniques allows the study of their plasma-driven photocatalytic reaction processes. In this study, we used gold nanostars (GNS) as the substrate to study its catalytic performance and sensitivity. On this basis, catalytic substrates of gold nanospheres (GNPs) were prepared for comparison. The catalytic reactions of PATP molecules on each of the above two substrates were systematically investigated under 633 nm laser irradiation. The reduction process was subsequently observed by introducing NaBH 4 solution. The results show that photocatalytic reactions can be achieved on both substrates under laser excitation at the same wavelength. However, the catalytic and reduction reaction rates on GNSs as a substrate are much faster than those of GNPs. This phenomenon may be due to the abundant nano-branched microstructures on the surface of GNSs, which will generate more and stronger local surface plasma hot spots under the irradiation of excitation light. In order to test the above hypothesis, the surface electromagnetic field distribution of two nanostructures was numerically simulated using the finite-difference time domain (FDTD) method. It is found that the star-like nanostructures not only have the same inter-particle hot spot system as the spherical nanostructures, but also have a large number of high-intensity single-particle hot spot systems arising from the abundance of branched nanostructures on their own surfaces. Compared with the spherical nanostructures, they are characterized by a dual hot spot system, which accelerates the photocatalytic reaction rate. The above experiments are of some reference significance for the in-depth study of multi-branched nanostructures and surface plasma distribution properties and their applications. (C) 2021 Elsevier B.V. All rights reserved.
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