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413 results on '"Li, Guiyin"'

30. A sandwich-type electrochemical sensor based on RGO-CeO2-Au nanoparticles and double aptamers for ultrasensitive detection of glypican-3.

Author

Liang, Jintao, Liang, Jianlu, Xiao, Xinkai, Guo, Fei, Zhan, Yulian, Zhou, Xueqing, Zhou, Zhide, and Li, Guiyin

Subjects
ELECTROCHEMICAL sensors, SANDWICH construction (Materials), CARRIER proteins, DETECTION limit, APTAMERS
Abstract

A sandwich-type electrochemical aptasensor for ultrasensitive detection of glypican-3 (GPC3) was constructed using GPC3 aptamer (GPC3Apt) labelled reduced graphene oxide-cerium oxide-gold nanoparticles (RGO-CeO2-Au NPs) as the signal probe and the same GPC3Apt as the capture probe. The electrochemical redox properties of CeO2 (Ce3+/Ce4+) in the RGO-CeO2-Au NPs indicate the electrochemical signals. When the target GPC3 was present, an "aptamer-protein-aptamer" sandwich structure was formed on the sensing interface due to the specific binding between the protein and aptamers, resulting in an increased electrochemical redox signal detected by differential pulse voltammetry (DPV) technique. Under optimal conditions, the established aptasensor exhibited a logarithmic linear relationship between the current response and GPC3 concentration in the range 0.001–100.0 ng/mL, with a minimum detection limit of 0.74 pg/mL. Using the spike-recovery tests for measurement of the human serum samples, the recovery was from 99.26 to 114.01%, and the RSD range was 3.04 to 5.34%. Furthermore, the sandwich-type electrochemical aptasensor exhibited excellent performance characteristics such as good stability, high specificity, and high sensitivity, demonstrating effective detection of GPC3 in human serum samples and can be used as a clinical detection tool for GPC3. [ABSTRACT FROM AUTHOR]

Published
2024
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35. A novel electrochemical aptasensor based on NrGO-H-Mn3O4 NPs integrated CRISPR/Cas12a system for ultrasensitive low-density lipoprotein determination.

Author

Li, Guiyin, Li, Shengnan, Li, Xinhao, He, Wei, Tan, Xiaohong, Liang, Jintao, and Zhou, Zhide

Subjects
*CRISPRS, *SINGLE-stranded DNA, *ELECTRIC conductivity, *LOW density lipoproteins, *DETECTION limit
Abstract

Atherosclerosis cardiovascular disease (ASCVD) has become one of the leading death causes in humans. Low-density lipoprotein (LDL) is an important biomarker for assessing ASCVD risk level. Thus, monitoring LDL levels can be an important means for early diagnosis of ASCVD. Herein, a novel electrochemical aptasensor for determination LDL was designed based on nitrogen-doped reduced graphene oxide-hemin-manganese oxide nanoparticles (NrGO-H-Mn3O4 NPs) integrated with clustered regularly interspaced short palindromic repeats and associated proteins (CRISPR/Cas12a) system. NrGO-H-Mn3O4 NPs not only have a large surface area and remarkable enhanced electrical conductivity but also the interconversion of different valence states of iron in hemin can provide an electrical signal. Nonspecific single-stranded DNA (ssDNA) was bound to NrGO-H-Mn3O4 NPs to form a signaling probe and was immobilized on the electrode surface. The CRISPR/Cas12a system has excellent trans-cleavage activity, which can be used to cleave ssDNA, thus detaching the NrGO-H-Mn3O4 NPs from the sensing interface and attenuating the electrical signal. Significant signal change triggered by the target was ultimately obtained, thus achieving sensitive detection of the LDL in range from 0.005 to 1000.0 nM with the detection limit of 0.005 nM. The proposed sensor exhibited good stability, selectivity, and stability and achieved reliable detection of LDL in serum samples, demonstrating its promising application prospects for the diagnostic application of LDL. [ABSTRACT FROM AUTHOR]

Published
2024
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36. Determination of difluoromethane (R32) by non-dispersive infrared (NDIR) spectroscopy with temperature compensation by an improved whale optimization algorithm (IWOA).

Author

Liang, Jintao, Wu, Liang, Wang, Liru, Li, Guiyin, Zhang, Tie, Zhang, Yonghuai, and Zhang, Jiayang

Subjects
METAHEURISTIC algorithms, BACK propagation, GAS detectors, SPECTROMETRY
Abstract

To reduce the influence of temperature on difluoromethane (R32) gas sensors using non-dispersive infrared (NDIR), a temperature compensation method based on improved whale optimization algorithm (IWOA) and back propagation neural network (BPNN) is proposed. The IWOA that uses tent chaotic mapping to optimize the initial population of the whale optimization algorithm (WOA) and incorporates adaptive weights in the population iterations is used to optimize the weights and thresholds between nodes in each layer of the BPNN. The optimized BPNN is used to train the temperature compensation model. The experimental results show that the back propagation neural network optimized with improved whale optimization algorithm (IWOA-BPNN) reduces the maximum relative error to 1.33%, compared to 12.46 and 11.66% for the traditional BPNN and the back propagation neural network optimized with whale optimization algorithm (WOA-BPNN), respectively. IWOA-BPNN is also compared with previously reported algorithms, and the results show that the algorithm improves the accuracy of the sensor. [ABSTRACT FROM AUTHOR]

Published
2024
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