scholarly journals Nano-evolution and protein-based enzymatic evolution predicts the novel types of natural product nanozyme of traditional Chinese medicine: cases of herbzymes of Taishan-Huangjing (Rhizoma polygonati) and Goji (Lycium chinense)

2021 ◽  
Author(s):  
Guldan Nazarbek ◽  
Aidana Kutzhanova ◽  
Lazzat Nurtay ◽  
Chenglin Mu ◽  
Bexultan Kazybay ◽  
...  
Keyword(s):  
Chinese Medicine ◽  
Traditional Chinese Medicine ◽  
Natural Product ◽  
Enzyme Function ◽  
The Novel ◽  
Lycium Chinense ◽  
Natural Protein

Nanozyme and natural product-derived herbzyme have been identified in different enzyme types simulating the natural protein-based enzyme function. How to explore and predict enzyme types of novel nanozyme when synthesized...

Retracted Article: A self-assembled supramolecular natural product gel from liquidambaric acid in traditional Chinese medicine with inherent anti-inflammatory activity for drug delivery

2020 ◽  
Vol 8 (4) ◽  
pp. 715-726 ◽  
Author(s):  
Kangkang Zhi ◽  
Jiacheng Wang
Keyword(s):  
Drug Delivery ◽  
Chinese Medicine ◽  
Traditional Chinese Medicine ◽  
Natural Product ◽  
Inflammatory Activity ◽  
Retracted Article ◽  
Anti Inflammatory ◽  
Self Assembled

A supramolecular self-assembled natural product gel from liquidambaric acid in traditional Chinese medicine with inherent anti-inflammatory activity for drug delivery was constructed.

scholarly journals Research Advance on Qingfei Paidu Decoction in Prescription Principle, Mechanism Analysis and Clinical Application

2021 ◽  
Vol 11 ◽  
Author(s):  
Wei Ren ◽  
Yue Ma ◽  
Raoqiong Wang ◽  
Pan Liang ◽  
Qin Sun ◽  
...  
Keyword(s):  
Chinese Medicine ◽  
Traditional Chinese Medicine ◽  
Clinical Application ◽  
Future Research ◽  
Mechanism Analysis ◽  
The Novel ◽  
Global Epidemic ◽  
State Administration ◽  
Tcm Theory ◽  
Novel Coronavirus

Since the sudden epidemic of coronavirus disease 2019 (COVID-19), the State Administration of Traditional Chinese Medicine immediately organized experts to formulate and screen the effective prescriptions of traditional Chinese medicine according to the characteristics of the novel coronavirus infection. Qingfei Paidu decoction (QFPDD) has been proven to be effective in multi-provincial clinical trials, and has been selected as a general prescription for the treatment of COVID-19 in different stages that was later promoted to be used nationwide. This review highlights the latest advances of QFPDD, focusing on the TCM theory, mechanism analysis, clinical application of QFPDD and its future perspectives. Moreover, an in-depth discussion of some valuable issues and possible development for future research on QFPDD is also discussed, aiming to provide a novel guide to combat the global epidemic COVID-19.

scholarly journals Research on the diagnosis and treatment of the dominant diseases of traditional Chinese medicine based on machine learning

2020 ◽  
Author(s):  
yuqi tang ◽  
Dongdong Yang ◽  
Zechen Li ◽  
Yu Fang ◽  
Shanshan Gao
Keyword(s):  
Machine Learning ◽  
Chinese Medicine ◽  
Random Forest ◽  
Traditional Chinese Medicine ◽  
Hierarchical Cluster ◽  
Diagnostic Methods ◽  
Diagnosis And Treatment ◽  
Syndrome Differentiation ◽  
The Novel ◽  
Sample Data

Abstract Background: Insomnia as one of the dominant diseases of traditional Chinese medicine (TCM) has been extensively studied in recent years. To explore the novel approaches of research on TCM diagnosis and treatment, this paper presents a strategy for the research of insomnia based on machine learning. Methods: First of all, 654 insomnia cases have been collected from an experienced doctor of TCM as sample data. Secondly, in the light of the characteristics of TCM diagnosis and treatment, the contents of research samples have been divided into four parts: the basic information, the four diagnostic methods, the treatment based on syndrome differentiation and the main prescription. And then, these four parts have been analyzed by three analysis methods, including frequency analysis, association rules and hierarchical cluster analysis. Finally, a comprehensive study of the whole four parts has been conducted by random forest. Results: Researches of the above four parts revealed some essential connections. Simultaneously, based on the algorithm model established by the random forest, the accuracy of predicting the main prescription by the combination of the four diagnostic methods and the treatment based on syndrome differentiation was 0.85. Furthermore, having been extracted features through applying the random forest, the syndrome differentiation of five zang-organs was proven to be the most significant parameter of the TCM diagnosis and treatment.Conclusions: The results indicate that the machine learning methods are worthy of being adopted to study the dominant diseases of TCM for exploring the crucial rules of the diagnosis and treatment.

scholarly journals Retraction: A self-assembled supramolecular natural product gel from liquidambaric acid in traditional Chinese medicine with inherent anti-inflammatory activity for drug delivery

2020 ◽  
Vol 8 (48) ◽  
pp. 11109-11109
Author(s):  
Kangkang Zhi ◽  
Jiacheng Wang
Keyword(s):  
Drug Delivery ◽  
Chinese Medicine ◽  
Traditional Chinese Medicine ◽  
Natural Product ◽  
Inflammatory Activity ◽  
Anti Inflammatory ◽  
Self Assembled

Retraction for ‘A self-assembled supramolecular natural product gel from liquidambaric acid in traditional Chinese medicine with inherent anti-inflammatory activity for drug delivery’ by Kangkang Zhi et al., J. Mater. Chem. B, 2020, 8, 715–726, DOI: 10.1039/C9TB02416F.

scholarly journals Artemether, Artesunate, Arteannuin B, Echinatin, Licochalcone B and Andrographolide Effectively Inhibit SARS-CoV-2 and Related Viruses In Vitro

2021 ◽  
Vol 11 ◽  
Author(s):  
Yunjia Hu ◽  
Meiqin Liu ◽  
Hongbo Qin ◽  
Haofeng Lin ◽  
Xiaoping An ◽  
...  
Keyword(s):  
Chinese Medicine ◽  
Traditional Chinese Medicine ◽  
Early Stage ◽  
Clinical Applications ◽  
The Novel ◽  
Compound Library ◽  
Global Pandemic ◽  
Novel Coronavirus ◽  
And Control

Since the first reported case caused by the novel coronavirus SARS-CoV-2 infection in Wuhan, COVID-19 has caused serious deaths and an ongoing global pandemic, and it is still raging in more than 200 countries and regions around the world and many new variants have appeared in the process of continuous transmission. In the early stage of the epidemic prevention and control and clinical treatment, traditional Chinese medicine played a huge role in China. Here, we screened out six monomer compounds, including artemether, artesunate, arteannuin B, echinatin, licochalcone B and andrographolide, with excellent anti-SARS-CoV-2 and anti-GX_P2V activity from Anti-COVID-19 Traditional Chinese Medicine Compound Library containing 389 monomer compounds extracted from traditional Chinese medicine prescriptions “three formulas and three drugs”. Our discovery preliminary proved the stage of action of those compounds against SARS-CoV-2 and provided inspiration for further research and clinical applications.

scholarly journals Anti-Apoptotic Role of Sanhuang Xiexin Decoction and Anisodamine in Endotoxemia

2021 ◽  
Vol 12 ◽  
Author(s):  
Zixuan Liu ◽  
Wenxiang Wang ◽  
Jie Luo ◽  
Yingrui Zhang ◽  
Yunsen Zhang ◽  
...  
Keyword(s):  
Septic Shock ◽  
Chinese Medicine ◽  
Traditional Chinese Medicine ◽  
Natural Product ◽  
Cell Apoptosis ◽  
Tissue Injury ◽  
Therapeutic Effects ◽  
Immune Paralysis ◽  
Apoptotic Mechanism

Endotoxemia is characterized by initial uncontrollable inflammation, terminal immune paralysis, significant cell apoptosis and tissue injury, which can aggravate or induce multiple diseases and become one of the complications of many diseases. Therefore, anti-inflammatory and anti-apoptotic therapy is a valuable strategy for the treatment of endotoxemia-induced tissue injury. Traditional Chinese medicine exhibits great advantages in the treatment of endotoxemia. In this review, we have analyzed and summarized the active ingredients and their metabolites of Sanhuang Xiexin Decoction, a famous formula in endotoxemia therapy. We then have summarized the mechanisms of Sanhuang Xiexin Decoction against endotoxemia and its mediated tissue injury. Furthermore, silico strategy was used to evaluate the anti-apoptotic mechanism of anisodamine, a well-known natural product that widely used to improve survival in patients with septic shock. Finally, we also have summarized other anti-apoptotic natural products as well as their therapeutic effects on endotoxemia and its mediated tissue injury.

scholarly journals Research of insomnia on traditional Chinese medicine diagnosis and treatment based on machine learning

2020 ◽  
Author(s):  
Yuqi Tang ◽  
Zechen Li ◽  
Dongdong Yang ◽  
Yu Fang ◽  
Shanshan Gao ◽  
...  
Keyword(s):  
Machine Learning ◽  
Chinese Medicine ◽  
Random Forest ◽  
Traditional Chinese Medicine ◽  
Hierarchical Cluster ◽  
Diagnostic Methods ◽  
Diagnosis And Treatment ◽  
Syndrome Differentiation ◽  
The Novel ◽  
Sample Data

Abstract Background: Insomnia as one of the dominant diseases of traditional Chinese medicine (TCM) has been extensively studied in recent years. To explore the novel approaches of research on TCM diagnosis and treatment, this paper presents a strategy for the research of insomnia based on machine learning. Methods: First of all, 654 insomnia cases have been collected from an experienced doctor of TCM as sample data. Secondly, in the light of the characteristics of TCM diagnosis and treatment, the contents of research samples have been divided into four parts: the basic information, the four diagnostic methods, the treatment based on syndrome differentiation and the main prescription. And then, these four parts have been analyzed by three analysis methods, including frequency analysis, association rules and hierarchical cluster analysis. Finally, a comprehensive study of the whole four parts has been conducted by random forest. Results: Researches of the above four parts revealed some essential connections. Simultaneously, based on the algorithm model established by the random forest, the accuracy of predicting the main prescription by the combinations of the four diagnostic methods and the treatment based on syndrome differentiation was 0.85. Furthermore, having been extracted features through applying the random forest, the syndrome differentiation of five zang-organs was proven to be the most significant parameter of the TCM diagnosis and treatment.Conclusions: The results indicate that the machine learning methods are worthy of being adopted to study the dominant diseases of TCM for exploring the crucial rules of the diagnosis and treatment.

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