MOLECULES
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2021
·Vol. 26
·期 22
·6855
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IF 4.412
Didi Ma,Lijun Wang,Yibao Jin,Lifei Gu,Xiean Yu,Xueqing Xie,Guo Yin,Jue Wang,Kaishun Bi,Yi Lu,Tiejie Wang
Rhodiola, especiallyRhodiola crenulateandRhodiola rosea, is an increasingly widely used traditional medicine or dietary supplement in Asian and western countries. Because of the phytochemical diversity and difference of therapeutic efficacy amongRhodiolaspecies, it is crucial to accurately identify them. In this study, a simple and efficient method of the classification ofRhodiola crenulate,Rhodiola rosea, and their confusable species (Rhodiola serrata,Rhodiola yunnanensis,Rhodiola kirilowiiandRhodiola fastigiate) was established by UHPLC fingerprints combined with chemical pattern recognition analysis. The results showed that similarity analysis and principal component analysis (PCA) could not achieve accurate classification among the sixRhodiolaspecies. Linear discriminant analysis (LDA) combined with stepwise feature selection exhibited effective discrimination. Seven characteristic peaks that are responsible for accurate classification were selected, and their distinguishing ability was successfully verified by partial least-squares discriminant analysis (PLS-DA) and orthogonal partial least-squares discriminant analysis (OPLS-DA), respectively. Finally, the components of these seven characteristic peaks were identified as 1-(2-Hydroxy-2-methylbutanoate) β-D-glucopyranose, 4-O-glucosyl-p-coumaric acid, salidroside, epigallocatechin, 1,2,3,4,6-pentagalloyglucose, epigallocatechin gallate, and (+)-isolarisiresinol-4′-O-β-D-glucopyranoside or (+)-isolarisiresinol-4-O-β-D-glucopyranoside, respectively. The results obtained in our study provided useful information for authenticity identification and classification ofRhodiolaspecies.Keywords:Rhodiola;UHPLC fingerprint;chemical pattern recognition;quality evaluation
研究领域:
药用植物学
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分析化学
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DOI
PubMed
高影响因子
ANALYTICAL CHEMISTRY
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2024
·
IF 6.7
Jing Zhu,Qing Hong Zhang,Wen Wu Wang
Exploiting the specific recognition probe for all of the biomolecules is difficult in “lock-and-key” biosensors. The cross-reaction or the semispecific probe in pattern recognition mode is an alternative strategy through extracting a multidimensional signal array from recognition elements. Here, we design a pattern recognition sensor array based on the alkaloid-inhibited catalytic activity of dopzymes for the discrimination and determination of six alkaloids. In this sensor array, three different G-rich sequences, i.e., G-triplex (G3), G-quadruplex (GQ1), and the G-quadruplex dimer (2GQ1) possessing various peroxidase activities, conjugated with a dopamine aptamer and the dopzymes (G3-d-apt, GQ1-d-apt, and 2GQ1-d-apt) were obtained with an enhanced catalytic performance for the substrate. Through the interactions between six target alkaloids and G3, GQ1, and 2GQ1 regions, the pattern signal (6 alkaloids × 3 dopzymes × 5 replicates) was obtained from the diverse inhibited effect for the dopzyme activity. In virtue of the statistical method principal component analysis (PCA), the data array was projected into a new dimensional space to acquire the three-dimensional (3D) canonical scores and grouped into their respective clusters. The sensor array exhibited an outstanding discrimination and classification capability for six alkaloids with different concentrations with 100% accuracy. In addition, the nonspecific recognition elements of the sensor array showed high selectivity even though other alkaloids with similar structures to targets existed in the samples. Importantly, the levels of the six targets can be analyzed by the most influential discrimination factor, which represented the vector with the highest variance, evidencing that the sensor array has potential in drug screening and clinical treatment.
研究领域:
生物化学
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药物分析
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医学检测
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DOI
PubMed
高影响因子
JOURNAL OF FOOD COMPOSITION AND ANALYSIS
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2024
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IF 4
Zhengfan Shui,Jiaying Zhao,Yunhui Li,Changjun Hou,Zhihua Li,Huibo Luo,Suyi Zhang,Yi Ma,Danqun Huo
Herein, a simple colorimetric sensor array sensitive to organic acids was designed by gold (Au) and silver (Ag) nanoparticles modified with four different compounds for the identification of 16 famous Baijius containing different organic acids. In detail, the sensing mechanism of the colorimetric sensor array was based on the charge transfer between the nanoparticle surface protectant and H + , which reduced the electrostatic force between the nanoparticles, leading to the aggregation and color change of the nanoparticles. The unique color change of the colorimetric array before and after the reaction was used as a unique fingerprint profile for each specific analyte, which can be identified by the naked eye. The generated digital database was analyzed using pattern recognition methods, including principal component analysis (PCA), hierarchical cluster analysis (HCA) and linear discriminant analysis (LDA). All Baijius can be easily identified by fingerprint mapping or PCA scoring maps. 32 blind samples were tested by LDA and 30 samples were correctly classified. The HCA results showed that all samples were correctly classified and even very similar 1 % dilutions of the Baijiu can be easily distinguished, demonstrating the potential of the constructed colorimetric sensor array technology for quality control applications of Baijius and other beverages.
研究领域:
分析化学
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食品科学
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DOI
高影响因子
ORGANIC ELECTRONICS
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2020
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IF 3.31
Jinsong Huang,Jinwei Chen,Rengjian Yu,Yilun Zhou,Qian Yang,Enlong Li,Qizhen Chen,Huipeng Chen,Tailiang Guo
Biodegradable and environmentally friendly artificial synapse devices are essential for the future development of neuromorphic computing . The emergence of synaptic transistors based on biocompatible polymer materials provides an ideal approach to achieve green electronics. However, modulating the synaptic properties in a wide range in a fixed biocompatible synaptic transistor is still challengeable, while it is vitally important for improving the adaptability of the synaptic device to achieve neuro-prosthetics in the future. Here, we reported the regulation of the synaptic behavior of biocompatible synaptic transistor through ion-doping, which allows to adjusting the response of the synaptic device according to a specific function. The ions doped into the insulating layer strengthen the formation of electric double layers (EDLs), which enables a remarkable regulation effect on post-synaptic current. Moreover, basic synaptic properties, including excitatory/inhibitory post-synaptic current (EPCS/IPSC), paired-pulse facilitation/depression (PPF/PPD), short-term/long-term memory (STM/LTM) are successfully demonstrated. In addition, high-pass and low-pass filtering functions are also implemented in a single synaptic device, indicating that the synapse attenuation can be effectively transformed according to the needs of the function. More importantly, this is the first work to demonstrate that the accuracy of pattern recognition of synaptic transistors, an important indicator of neuromorphic calculations, can be significantly improved via ion doping (as high as 75.96% relative to undoped devices of 41.68%). Our research provides a feasible strategy for precisely controlling synaptic behaviors, which has a profound impact on improving the adaptability of artificial synaptic devices in the field of neuromorphic computing.
研究领域:
神经形态计算
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材料科学
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电子工程
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DOI
高影响因子
JOURNAL OF FOOD COMPOSITION AND ANALYSIS
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2025
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IF 4.6
Xia Hua,Chunling Yin,Leqian Hu,Liuchuang Zhao,Zhimin Liu,Peng Li
s Selective probes exclusively interact with a single metal ion species. In contrast, weakly selective probes can simultaneously coordinate with multiple metal ions, generating distinct fluorescence spectral signatures. This unique attribute enables them to provide more abundant chemical information. In this study, two weakly selective fluorescent probes of imidazole derivatives were designed and synthesized. We investigated the viability of utilizing a fluorescent array to trace the origin of Poria cocos based on the variations in fluorescence intensity and position of the distinctive fluorescence peaks created by their interaction with various metal ions. Subsequently, we collected three-dimensional fluorescence spectra of the interactions between the fluorescent array sensors and Poria cocos extracts from different geographical origins. These array data were analyzed using multi-way pattern recognition methods. The U-PLS-DA model exhibited excellent performance, with a prediction accuracy of 97.56 % that exceeded that of the N-PLS-DA model. This study demonstrates that the weakly selective probe array approach integrated with chemometric analysis provides a novel strategy for the traceability of non-fluorescent foods and traditional Chinese medicines.
研究领域:
分析化学
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药物分析
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中药学
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化学计量学
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荧光探针技术
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DOI
高影响因子
Electronics
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2025
·Vol. 14
·期 6
·1183
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IF 2.6
Liwei Zhang,Sixing Chen,Shaoming Fu,Songjia Han,Li Zhang,Yu Zhang,Mengye Wang,Chuan Liu,Xiaoci Liang
WO3-based electrochemical transistors (ECTs) are recognized as candidates for three-terminal memristors due to their high on–off ratio, long retention time, and rapid switching speed. However, their patterned fabrication often relies on complex vacuum systems or extreme processing conditions, hindering cost-effective scalability. Here, we developed a novel wet etching technique integrated with sol–gel-derived WO3channels, enabling ambient-air fabrication of Nafion-WO3ECTs. The wet-etched devices achieve an on–off ratio of ~105, surpassing unetched and dry-etched counterparts by orders of magnitude. Furthermore, they exhibit exceptional paired-pulse facilitation and long-term stability, maintaining 12 distinct conductance states for 103s, and an on–off ratio of ~102over 25 read–write cycles. XPS result shows higher W5+content and M-O-H bond proportion for wet-etched devices, revealing an optimized interface, with enhanced H+injection efficiency. The simulated artificial neural network using this wet-etched ECT shows ~97% recognition accuracy for handwritten numerals. This approach offers a novel patterning strategy for developing cost-effective, high-performance neuromorphic devices.
研究领域:
材料科学
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神经科学
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电子工程
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DOI
高影响因子
Advanced Intelligent Systems
·
2022
·Vol. 4
·期 12
·2200169
·
IF 7.298
Wenjie Ren,Changhui Zhao,Gaoqiang Niu,Yi Zhuang,Fei Wang
Artificial senses like electronic nose, which ameliorates the problem of poor selectivity from single gas sensor, have elicited keen research interest to monitor hazardous gases. Herein, the doping effects of gallium on In 2 O 3 nanotubes (NTs) are investigated and a four-component sensor array for the detection of trimethylamine (TMA) is reported. All-gallium-doped/alloyed In 2 O 3 (Ga-In 2 O 3 ) sensors show improved sensitivity and selectivity to TMA at an operating temperature of 240 °C, with 5 mol% Ga-doped/alloyed one displaying the highest response in the range of 0.5–100 ppm and the lowest detection limit of 13.83 ppb. Based on the gas-sensing properties, a four-component sensor array is fabricated, which shows unique response patterns in variable-gas backgrounds. Herein, back propagation neural network (BPNN), radial basis function neural network (RBFNN), and principal component analysis-based linear regression (PCA-LR) are trained with the gas-sensing data to discriminate different gases with high accuracy, as well as to predict the concentrations of target gases in different gases and gas mixtures. Furthermore, accuracies of 92.85% and 99.14% can be achieved for the classification of six gases (three single gases and three binary gas mixtures) and for the prediction of TMA concentrations in the presence of different concentrations of TMA and acetone, respectively.
研究领域:
材料科学
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电子工程
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化学
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DOI
高影响因子
MOLECULES
·
2023
·Vol. 28
·期 16
·6063
·
IF 4.6
Yali Guo,Bing Wang,Lifei Gu,Guo Yin,Shuhong Wang,Meifang Li,Lijun Wang,Xie-An Yu,Tiejie Wang
The fraud phenomenon is currently widespread in the traditional Chinese medicine Radix Astragali (RA) market, especially where high-quality RA is substituted with low-quality RA. In this case, focused on polysaccharides from RA, the classification models were established for discrimination of RA from different growth patterns, origins, species, and growth years. 1H Nuclear Magnetic Resonance (H1-NMR) was used to establish the spectroscopy of polysaccharides from RA, which were used to distinguish RA via chemical pattern recognition methods. Specifically, orthogonal partial least squares discriminant analysis (OPLS-DA) and linear discriminant analysis (LDA) were used to successfully establish the classification models for RA from different growth patterns, origins, species, and growth years. The satisfactory parameters and high accuracy of internal and external verification of each model exhibited the reliable and good prediction ability of the developed models. In addition, the polysaccharide content and immunological activity were also tested, which was evaluated by the phagocytic activity of RAW 264.7. And the result showed that growth patterns and origins significantly affected the quality of RA. However, there was no significant difference in the aspects of origins and growth years. Accordingly, the developed strategy combined with chemical information, biological activity, and multivariate statistical method can provide new insight for the quality evaluation of traditional Chinese medicine.Keywords:Radix Astragali;immunomodulatory activity;polysaccharide content;chemical pattern recognition;quality evaluation
研究领域:
中药学
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生物化学
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分析化学
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DOI
PubMed
高影响因子
Sensors & Diagnostics
·
2022
·Vol. 2
·期 1
·188-193
·
IF 0
Xiaowei Liu,Zhiwei Zhang,Xuetao Yan,Xinying Zhang,Francois Amblard,Yingying Chen,Lingyan Feng
An artificial tongue for the discrimination of different metal ions based on fluorescent carbon dots (C-dots) and meso-tetrakis(4-(N-methylpyridiumyl))porphyrin (TMPyP) was developed in this manuscript. Fluorescence resonance energy transfer (FRET) between C-dots and TMPyP was applied for the sensor array consisting of C-dots, TMPyP and a C-dot–TMPyP complex. Fifteen metal ions have been effectively identified by the sensor array with different fingerprint-like patterns which were analyzed from the distinct fluorescence responses through principal component analysis (PCA) and hierarchical cluster analysis (HCA), providing a fast and efficient method for the detection of metal ions.
研究领域:
分析化学
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材料科学
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DOI
Nano Energy
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2024
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IF 16.8
Xinrong Zhi,Shifan Ma,Yifan Xia,Biao Yang,Siyu Zhang,Kangting Liu,Mingyuan Li,Shuhan Li,Wan Peiyuan,Xin Wang
Tactile sensor as core component of robotic haptics enables intelligent perception of external environment for smart robot. However, it is a critical challenge to realize simultaneously high-sensitivity pressure sensing and high-resolution tactile imaging of tactile sensor. Herein, a hierarchical hybrid tactile sensor array (HTSA), which is fabricated by vertically integrating top arrayed TENG layer and bottom arrayed capacitive pressure sensor layer, is developed to achieve simultaneous pressure sensing and tactile imaging for tactile pattern recognition. The capacitive pressure sensor array (8 × 8) can realize pressure sensing with a sensitivity of 238.73 kPa −1 . Meanwhile, the TENG-based tactile sensing array enables high-resolution tactile imaging of handwritten Chinese characters. More importantly, the HTSA-based tactile pattern recognition system (H-TPRS) is developed to achieve accurate user signature authentication. Based on handwriting behavior characteristics, an accuracy of 97.3% of tactile pattern recognition is achieved in identifying the different-user handwriting identical letters under assistance of convolutional neural network . Consequently, the H-TPRS can achieve high-sensitivity pressure sensing and high-resolution tactile imaging of Chinese characters for user authentication, which demonstrates potential application in the field of intelligent tactile perception .
研究领域:
机器人学
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材料科学
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人工智能
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产品关联
DOI
高影响因子
PHYTOCHEMICAL ANALYSIS
·
2024
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IF 3
Yangling Li,Ying Su,Yongjuan Liang,Fangchan Li,Ning Lin,Lin Jiang,Qinghua Lin,Qing Chen
Introduction Kidney tea is an essential herbal medicine. It is widely used to treat conditions such as urinary stones, gallstones, and rheumatoid arthritis. There is currently no standardized or widely accepted research strategy for evaluating the quality of kidney tea granules (KTGs) after granulation. Objectives In this study, we aim to establish a comprehensive strategy for evaluating the quality of KTGs produced from different sources of kidney tea. Methods A TLC combined with HPLC method was established to identify the chemical components in KTGs, and HPLC method was used to determine the contents of rosmarinic acid of KTGs. In order to distinguish samples and identify differential components, similarity analysis, hierarchical cluster analysis (HCA), principal component analysis (PCA), and orthogonal partial least squares discriminant analysis (OPLS-DA) were conducted. Results TLC and HPLC detection confirmed three chemical components of KTGs, which are rosmarinic acid, caffeic acid, and lithospermic acid. HPLC fingerprint analysis revealed a total of seven common peaks in 15 batches of KTGs. Similarity analysis showed that the similarity of all 15 batches of KTGs was greater than 0.969. The peak areas of the seven common peaks were identified by chemical pattern recognition, and the results showed that most of the KTGs from different origins were clustered together, with small differences between them. The PCA and OPLS-DA results showed that two principal components can represent 82.638% of the common peaks of KTGs, among which peak 5 represents rosmarinic acid, which is the main differential biomarker of KTGs from different regions. Quantitative analysis of rosmarinic acid in KTG samples was performed using HPLC fingerprint conditions and the content of rosmarinic acid in 15 batches of KTGs samples was measured to be between 8.01–14.61 mg/g. Conclusion This study combines TLC, HPLC, and chemometrics to establish a stable and reliable method that can quickly and effectively identify the components of KTGs, accurately quantify known components in KTGs, and provide reference for the quality evaluation of KTGs.
研究领域:
中药学
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分析化学
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产品关联
DOI
PubMed
高影响因子
Nature Communications
·
2022
·Vol. 13
·期 1
·1-12
·
IF 17.694
Tian Jia-Hong,Hu Xin-Yue,Hu Zong-Ying,Tian Han-Wen,Li Juan-Juan,Pan Yu-Chen,Li Hua-Bin,Guo Dong-Sheng
Differential sensing, which discriminates analytes via pattern recognition by sensor arrays, plays an important role in our understanding of many chemical and biological systems. However, it remains challenging to develop new methods to build a sensor unit library without incurring a high workload of synthesis. Herein, we propose a supramolecular approach to construct a sensor unit library by taking full advantage of recognition and assembly. Ten sensor arrays are developed by replacing the building block combinations, adjusting the ratio between system components, and changing the environment. Using proteins as model analytes, we examine the discriminative abilities of these supramolecular sensor arrays. Then the practical applicability for discriminating complex analytes is further demonstrated using honey as an example. This sensor array construction strategy is simple, tunable, and capable of developing many sensor units with as few syntheses as possible.
研究领域:
分析化学
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超分子化学
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生物传感器
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DOI
PubMed
高影响因子
危险品化学品经营许可证（带存储）