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196 results on '"Tong, Zhaoyang"'

31. Performance of Classification Models of Toxins Based on Raman Spectroscopy Using Machine Learning Algorithms.

Author

Zhang, Pengjie, Liu, Bing, Mu, Xihui, Xu, Jiwei, Du, Bin, Wang, Jiang, Liu, Zhiwei, and Tong, Zhaoyang

Subjects
MACHINE learning, PARTIAL least squares regression, RAMAN spectroscopy, RICIN, TOXINS, BACTERIAL toxins, DISCRIMINANT analysis
Abstract

Rapid and accurate detection of protein toxins is crucial for public health. The Raman spectra of several protein toxins, such as abrin, ricin, staphylococcal enterotoxin B (SEB), and bungarotoxin (BGT), have been studied. Multivariate scattering correction (MSC), Savitzky–Golay smoothing (SG), and wavelet transform methods (WT) were applied to preprocess Raman spectra. A principal component analysis (PCA) was used to extract spectral features, and the PCA score plots clustered four toxins with two other proteins. The k-means clustering results show that the spectra processed with MSC and MSC-SG methods have the best classification performance. Then, the two data types were classified using partial least squares discriminant analysis (PLS-DA) with an accuracy of 100%. The prediction results of the PCA and PLS-DA and the partial least squares regression model (PLSR) perform well for the fingerprint region spectra. The PLSR model demonstrates excellent classification and regression ability (accuracy = 100%, Rcv = 0.776). Four toxins were correctly classified with interference from two proteins. Classification models based on spectral feature extraction were established. This strategy shows excellent potential in toxin detection and public health protection. These models provide alternative paths for the development of rapid detection devices. [ABSTRACT FROM AUTHOR]

Published
2024
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35. A signal-off photoelectrochemical sandwich-type immunosensor based on WO3/TiO2 Z-scheme heterojunction.

Author

Pei, Fubin, Feng, Shasha, Hu, Wei, Hao, Qingli, Liu, Bing, Mu, Xihui, Lei, Wu, and Tong, Zhaoyang

Subjects
TUNGSTEN trioxide, SARS-CoV-2, ELECTRON paramagnetic resonance spectroscopy, HETEROJUNCTIONS
Abstract

A sandwich "signal-off" type photoelectrochemical (PEC) immunosensor was fabricated based on a composite heterojunction of tungsten oxide/titanium oxide microspheres (WO3/TiO2) acting as signal amplification platform and carbon microspheres loaded by gold nanoparticles (Cs@Au NPs) utilized as the label for detecting antibody. WO3/TiO2 had excellent photoelectric performance, and the results of Mott-Schottky plots, open-circuit voltage, and electron spin resonance spectroscopy indicated that it belonged to the Z-scheme heterojunction transfer mechanism of photogenerated carriers. To achieve the sensitization of PEC immunosensor, Cs@Au NP–labeled immunocomplex can effectively reduce the photocurrent signal. The PEC immunosensors were fabricated under the optimal conditions of 1:1 WO3/TiO2 (molar ratio), 2.0 mg mL−1 WO3/TiO2, and 1.5 mg mL−1 Cs@Au NPs. Through comparison of the detection results of label-free and sandwich-type PEC immunosensors for nucleocapsid (N) protein of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), we found that the sensitivity of the sandwich type was 2.53 times the label-free type, and the limit of detection was 0.006 ng mL−1, i.e., 3.17 times lower than the label-free type. This demonstrates that the developed sandwich-type PEC immunosensor will have a brighter application prospect. [ABSTRACT FROM AUTHOR]

Published
2023
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47. Surface Plasmon Resonance Sensor Based on Core-Shell Fe 3 O 4 @SiO 2 @Au Nanoparticles Amplification Effect for Detection of T-2 Toxin.

Author

Fan, Lirui, Du, Bin, Pei, Fubin, Hu, Wei, Guo, Aijiao, Xie, Zihao, Liu, Bing, Tong, Zhaoyang, Mu, Xihui, and Tan, Wenyuan

Subjects
IRON oxides, SURFACE plasmon resonance, RICIN, SMALL molecules, NANOPARTICLES
Abstract

In this paper, a core-shell based on the Fe3O4@SiO2@Au nanoparticle amplification technique for a surface plasmon resonance (SPR) sensor is proposed. Fe3O4@SiO2@AuNPs were used not only to amplify SPR signals, but also to rapidly separate and enrich T-2 toxin via an external magnetic field. We detected T-2 toxin using the direct competition method in order to evaluate the amplification effect of Fe3O4@SiO2@AuNPs. A T-2 toxin–protein conjugate (T2-OVA) immobilized on the surface of 3-mercaptopropionic acid-modified sensing film competed with T-2 toxin to combine with the T-2 toxin antibody–Fe3O4@SiO2@AuNPs conjugates (mAb-Fe3O4@SiO2@AuNPs) as signal amplification elements. With the decrease in T-2 toxin concentration, the SPR signal gradually increased. In other words, the SPR response was inversely proportional to T-2 toxin. The results showed that there was a good linear relationship in the range of 1 ng/mL~100 ng/mL, and the limit of detection was 0.57 ng/mL. This work also provides a new possibility to improve the sensitivity of SPR biosensors in the detection of small molecules and in disease diagnosis. [ABSTRACT FROM AUTHOR]

Published
2023
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