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Fuzzy identification of bioactive components for different efficacies of rhubarb by the back propagation neural network association analysis of UPLC-Q-TOF/MS(E) and integrated effects
BACKGROUND: Rhei Radix et Rhizoma (rhubarb), as one of the typical representatives of multi-effect traditional Chinese medicines (TCMs), has been utilized in the treatment of various diseases due to its multicomponent nature. However, there are few systematic investigations for the corresponding eff...
Autores principales: | , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9040240/ https://www.ncbi.nlm.nih.gov/pubmed/35473719 http://dx.doi.org/10.1186/s13020-022-00612-9 |
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author | Chen, Jia-Qian Chen, Yan-Yan Du, Xia Tao, Hui-Juan Pu, Zong-Jin Shi, Xu-Qin Yue, Shi-Jun Zhou, Gui-Sheng Shang, Er-Xin Tang, Yu-Ping Duan, Jin-Ao |
author_facet | Chen, Jia-Qian Chen, Yan-Yan Du, Xia Tao, Hui-Juan Pu, Zong-Jin Shi, Xu-Qin Yue, Shi-Jun Zhou, Gui-Sheng Shang, Er-Xin Tang, Yu-Ping Duan, Jin-Ao |
author_sort | Chen, Jia-Qian |
collection | PubMed |
description | BACKGROUND: Rhei Radix et Rhizoma (rhubarb), as one of the typical representatives of multi-effect traditional Chinese medicines (TCMs), has been utilized in the treatment of various diseases due to its multicomponent nature. However, there are few systematic investigations for the corresponding effect of individual components in rhubarb. Hence, we aimed to develop a novel strategy to fuzzily identify bioactive components for different efficacies of rhubarb by the back propagation (BP) neural network association analysis of ultra-performance liquid chromatography/quadrupole time-of-flight mass spectrometry for every data (UPLC-Q-TOF/MS(E)) and integrated effects. METHODS: Through applying the fuzzy chemical identification, most components of rhubarb were classified into different chemical groups. Meanwhile the integration effect values of different efficacies can be determined by animal experiment evaluation and multi-attribute comprehensive indexes. Then the BP neural network was employed for association analysis of components and different efficacies by correlating the component contents determined from UPLC-Q-TOF/MS(E) profiling and the integration effect values. Finally, the effect contribution of one type of components may be totaled to demonstrate the universal and individual characters for different efficacies of rhubarb. RESULTS: It suggested that combined anthraquinones, flavanols and their polymers may be the universal character to the multi-functional properties of rhubarb. Other components contributed to the individuality of rhubarb efficacies, including stilbene glycosides, anthranones and their dimers, free anthraquinones, chromones, gallic acid and gallotannins, butyrylbenzenes and their glycosides. CONCLUSIONS: Our findings demonstrated that the bioactive components for different efficacies of rhubarb were not exactly the same and can be systematically differentiated by the network-oriented strategy. These efforts will advance our knowledge and understanding of the bioactive components in rhubarb and provide scientific evidence to support the expansion of its use in clinical applications and the further development of some products based on this medicinal herb. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s13020-022-00612-9. |
format | Online Article Text |
id | pubmed-9040240 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-90402402022-04-27 Fuzzy identification of bioactive components for different efficacies of rhubarb by the back propagation neural network association analysis of UPLC-Q-TOF/MS(E) and integrated effects Chen, Jia-Qian Chen, Yan-Yan Du, Xia Tao, Hui-Juan Pu, Zong-Jin Shi, Xu-Qin Yue, Shi-Jun Zhou, Gui-Sheng Shang, Er-Xin Tang, Yu-Ping Duan, Jin-Ao Chin Med Research BACKGROUND: Rhei Radix et Rhizoma (rhubarb), as one of the typical representatives of multi-effect traditional Chinese medicines (TCMs), has been utilized in the treatment of various diseases due to its multicomponent nature. However, there are few systematic investigations for the corresponding effect of individual components in rhubarb. Hence, we aimed to develop a novel strategy to fuzzily identify bioactive components for different efficacies of rhubarb by the back propagation (BP) neural network association analysis of ultra-performance liquid chromatography/quadrupole time-of-flight mass spectrometry for every data (UPLC-Q-TOF/MS(E)) and integrated effects. METHODS: Through applying the fuzzy chemical identification, most components of rhubarb were classified into different chemical groups. Meanwhile the integration effect values of different efficacies can be determined by animal experiment evaluation and multi-attribute comprehensive indexes. Then the BP neural network was employed for association analysis of components and different efficacies by correlating the component contents determined from UPLC-Q-TOF/MS(E) profiling and the integration effect values. Finally, the effect contribution of one type of components may be totaled to demonstrate the universal and individual characters for different efficacies of rhubarb. RESULTS: It suggested that combined anthraquinones, flavanols and their polymers may be the universal character to the multi-functional properties of rhubarb. Other components contributed to the individuality of rhubarb efficacies, including stilbene glycosides, anthranones and their dimers, free anthraquinones, chromones, gallic acid and gallotannins, butyrylbenzenes and their glycosides. CONCLUSIONS: Our findings demonstrated that the bioactive components for different efficacies of rhubarb were not exactly the same and can be systematically differentiated by the network-oriented strategy. These efforts will advance our knowledge and understanding of the bioactive components in rhubarb and provide scientific evidence to support the expansion of its use in clinical applications and the further development of some products based on this medicinal herb. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s13020-022-00612-9. BioMed Central 2022-04-26 /pmc/articles/PMC9040240/ /pubmed/35473719 http://dx.doi.org/10.1186/s13020-022-00612-9 Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data. |
spellingShingle | Research Chen, Jia-Qian Chen, Yan-Yan Du, Xia Tao, Hui-Juan Pu, Zong-Jin Shi, Xu-Qin Yue, Shi-Jun Zhou, Gui-Sheng Shang, Er-Xin Tang, Yu-Ping Duan, Jin-Ao Fuzzy identification of bioactive components for different efficacies of rhubarb by the back propagation neural network association analysis of UPLC-Q-TOF/MS(E) and integrated effects |
title | Fuzzy identification of bioactive components for different efficacies of rhubarb by the back propagation neural network association analysis of UPLC-Q-TOF/MS(E) and integrated effects |
title_full | Fuzzy identification of bioactive components for different efficacies of rhubarb by the back propagation neural network association analysis of UPLC-Q-TOF/MS(E) and integrated effects |
title_fullStr | Fuzzy identification of bioactive components for different efficacies of rhubarb by the back propagation neural network association analysis of UPLC-Q-TOF/MS(E) and integrated effects |
title_full_unstemmed | Fuzzy identification of bioactive components for different efficacies of rhubarb by the back propagation neural network association analysis of UPLC-Q-TOF/MS(E) and integrated effects |
title_short | Fuzzy identification of bioactive components for different efficacies of rhubarb by the back propagation neural network association analysis of UPLC-Q-TOF/MS(E) and integrated effects |
title_sort | fuzzy identification of bioactive components for different efficacies of rhubarb by the back propagation neural network association analysis of uplc-q-tof/ms(e) and integrated effects |
topic | Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9040240/ https://www.ncbi.nlm.nih.gov/pubmed/35473719 http://dx.doi.org/10.1186/s13020-022-00612-9 |
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