Large-Scale Isolation and Antitumor Mechanism Evaluation of Compounds from the Traditional Chinese Medicine Cordyceps Militaris

Background: Radix Sophorae flavescentis (Kushen), a Chinese herb, is widely used in the treatment of ulcerative colitis (UC) with damp-heat accumulation syndrome (DHAS) according to traditional Chinese medicine (TCM) theory.Objective: The aim of this study was to illuminate the clinical efficacy and potential mechanisms of Kushen-based TCM formulations in the treatment of UC with DHAS.Materials and Methods: A systematic literature search was performed in the PubMed, EMBASE, Chinese Biomedical Literature database, China National Knowledge Infrastructure database, Chongqing VIP Information database, and Wanfang database for articles published between January 2000 and July 2020 on randomized controlled trials (RCTs) that used Kushen-based TCM formulations in the treatment of UC with DHAS. A network pharmacology approach was conducted to detect the potential pathways of Kushen against UC with DHAS.Results: Eight RCTs with a total of 983 subjects were included in the meta-analysis. Compared with the control subjects (5-aminosalicylic acid therapy), those who received Kushen-based TCM formulations for the treatment of UC showed a significantly higher clinical remission rate (RR = 1.20, 95% CI: [1.04, 1.38], p = 0.02) and lower incidence of adverse events (RR = 0.63, 95% CI [0.39, 1.01], p = 0.06). A component-target-pathway network was constructed, indicating five main components (quercetin, luteolin, matrine, formononetin, and phaseolin), three major targets (Interleukin-6, Myc proto-oncogene protein, and G1/S-specific cyclin-D1) and one key potential therapeutic pathway (PI3K-Akt signaling) of Kushen against UC with DHAS.Conclusion: Kushen-based TCM formulations provide good efficacy and possess great potential in the treatment of UC. Large-scale and high-quality clinical trials and experimental verification should be considered for further confirmation of the efficacy of Kushen-based formulations.

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Predicting the Drug Safety for Traditional Chinese Medicine through a Comparative Analysis of Withdrawn Drugs Using Pharmacological Network

Evidence-based Complementary and Alternative Medicine ◽

10.1155/2013/256782 ◽

2013 ◽

Vol 2013 ◽

pp. 1-11 ◽

Cited By ~ 5

Author(s):

Mengzhu Xue ◽

Shoude Zhang ◽

Chaoqian Cai ◽

Xiaojuan Yu ◽

Lei Shan ◽

...

Keyword(s):

Clinical Trials ◽

Natural Products ◽

Chinese Medicine ◽

Traditional Chinese Medicine ◽

Drug Safety ◽

Large Scale ◽

Drug Candidate ◽

Topology Analysis ◽

Drug Safety Surveillance ◽

Approved Drugs

As the major issue to limit the use of drugs, drug safety leads to the attrition or failure in clinical trials of drugs. Therefore, it would be more efficient to minimize therapeutic risks if it could be predicted before large-scale clinical trials. Here, we integrated a network topology analysis with cheminformatics measurements on drug information from the DrugBank database to detect the discrepancies between approved drugs and withdrawn drugs and give drug safety indications. Thus, 47 approved drugs were unfolded with higher similarity measurements to withdrawn ones by the same target and confirmed to be already withdrawn or discontinued in certain countries or regions in subsequent investigations. Accordingly, with the 2D chemical fingerprint similarity calculation as a medium, the method was applied to predict pharmacovigilance for natural products from an in-house traditional Chinese medicine (TCM) database. Among them, Silibinin was highlighted for the high similarity to the withdrawn drug Plicamycin although it was regarded as a promising drug candidate with a lower toxicity in existing reports. In summary, the network approach integrated with cheminformatics could provide drug safety indications effectively, especially for compounds with unknown targets or mechanisms like natural products. It would be helpful for drug safety surveillance in all phases of drug development.

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Detection of Herb-Symptom Associations from Traditional Chinese Medicine Clinical Data

Evidence-based Complementary and Alternative Medicine ◽

10.1155/2015/270450 ◽

2015 ◽

Vol 2015 ◽

pp. 1-11 ◽

Cited By ~ 2

Author(s):

Yu-Bing Li ◽

Xue-Zhong Zhou ◽

Run-Shun Zhang ◽

Ying-Hui Wang ◽

Yonghong Peng ◽

...

Keyword(s):

Chinese Medicine ◽

Traditional Chinese Medicine ◽

Clinical Data ◽

Multiple Testing ◽

Large Scale ◽

Individualized Medicine ◽

Correlation Method ◽

Data Sets ◽

Chi Square ◽

Positive Correlations

Background. Traditional Chinese medicine (TCM) is an individualized medicine by observing the symptoms and signs (symptoms in brief) of patients. We aim to extract the meaningful herb-symptom relationships from large scale TCM clinical data.Methods. To investigate the correlations between symptoms and herbs held for patients, we use four clinical data sets collected from TCM outpatient clinical settings and calculate the similarities between patient pairs in terms of the herb constituents of their prescriptions and their manifesting symptoms by cosine measure. To address the large-scale multiple testing problems for the detection of herb-symptom associations and the dependence between herbs involving similar efficacies, we propose a network-based correlation analysis (NetCorrA) method to detect the herb-symptom associations.Results. The results show that there are strong positive correlations between symptom similarity and herb similarity, which indicates that herb-symptom correspondence is a clinical principle adhered to by most TCM physicians. Furthermore, the NetCorrA method obtains meaningful herb-symptom associations and performs better than the chi-square correlation method by filtering the false positive associations.Conclusions. Symptoms play significant roles for the prescriptions of herb treatment. The herb-symptom correspondence principle indicates that clinical phenotypic targets (i.e., symptoms) of herbs exist and would be valuable for further investigations.

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Traditional Chinese Medicine Reduces the Incidence of Chemotherapy-Induced Stroke: A Five-Year Nationwide Population-Based Cohort Study From Taiwan

Frontiers in Pharmacology ◽

10.3389/fphar.2021.614606 ◽

2021 ◽

Vol 12 ◽

Author(s):

Chien-Chen Huang ◽

Yu-Cih Yang ◽

Iona MacDonald ◽

Ching-Yuan Lai ◽

Cheng-Hao Tu ◽

...

Keyword(s):

Risk Factor ◽

Chinese Medicine ◽

Traditional Chinese Medicine ◽

Large Scale ◽

Population Based ◽

Incidence Rates ◽

First Year ◽

Subdistribution Hazard ◽

Stroke Incidence ◽

Kaplan Meier

Background: Chemotherapy is suspected to be a risk factor for stroke in patients with cancer, athough the results from large-scale studies are controversial. Few strategies are available for reducing the stroke-related risks.Methods: We analyzed stroke incidence rates in Taiwan’s Longitudinal Health Insurance database 2000 (LHID2000) for patients aged ≥20 years with newly-diagnosed cancer between Jan 1, 2000 and Dec 31, 2006, who did or did not receive chemotherapy. Moreover, we compared stroke incidence rates among chemotherapy users who did or did not use traditional Chinese medicine. All study participants were followed-up for 5 years or until they had a stroke.Results: In adjusted Kaplan-Meier analysis, the incidence of stroke was higher within the first year of cancer diagnosis among chemotherapy recipients compared with those who did not receive chemotherapy (31.1 vs. 9.75; adjusted subdistribution hazard ratio [sHR] 2.21; 95% confidence interval [CI], 1.52–3.20; p < 0.001). This between-group difference persisted at 4 years of follow-up (13.6 vs. 5.42; adjusted sHR 1.94; 95% CI, 1.53–2.46; p < 0.001). Similarly, the 5-year incidence rate of stroke was significantly lower among chemotherapy recipients using TCM vs. non-TCM users (0.19 vs. 0.46; adjusted sHR 0.45; 95% CI, 0.26–0.79; p < 0.001), as was the mortality rate (adjusted sHR 0.55; 95% CI, 0.44–0.68; p < 0.001).Conclusion: These Taiwanese data suggest that chemotherapy is a risk factor for stroke and that the use of TCM can significantly mitigate this risk. TCM also appears to reduce the mortality risk associated with chemotherapy.

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AMFormulaS: an intelligent retrieval system for traditional Chinese medicine formulas

BMC Medical Informatics and Decision Making ◽

10.1186/s12911-021-01419-8 ◽

2021 ◽

Vol 21 (S2) ◽

Author(s):

Yidi Cui ◽

Bo Gao ◽

Lihong Liu ◽

Jing Liu ◽

Yan Zhu

Keyword(s):

Statistical Analysis ◽

Chinese Medicine ◽

Traditional Chinese Medicine ◽

Search Engine ◽

Large Scale ◽

Retrieval System ◽

Small Scale ◽

Efficient Retrieval ◽

Efficient Information ◽

Retrieval Engine

Abstract Background Formula is an important means of traditional Chinese medicine (TCM) to treat diseases and has great research significance. There are many formula databases, but accessing rich information efficiently is difficult due to the small-scale data and lack of intelligent search engine. Methods We selected 38,000 formulas from a semi-structured database, and then segmented text, extracted information, and standardized terms. After that, we constructed a structured formula database based on ontology and an intelligent retrieval engine by calculating the weight of decoction pieces of formulas. Results The intelligent retrieval system named AMFormulaS (means Ancient and Modern Formula system) was constructed based on the structured database, ontology, and intelligent retrieval engine, so the retrieval and statistical analysis of formulas and decoction pieces were realized. Conclusions AMFormulaS is a large-scale intelligent retrieval system which includes a mass of formula data, efficient information extraction system and search engine. AMFormulaS could provide users with efficient retrieval and comprehensive data support. At the same time, the statistical analysis of the system can enlighten scientific research ideas and support patent review as well as new drug research and development.

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Sustainable Utilization of Traditional Chinese Medicine Resources: Systematic Evaluation on Different Production Modes

Evidence-based Complementary and Alternative Medicine ◽

10.1155/2015/218901 ◽

2015 ◽

Vol 2015 ◽

pp. 1-10 ◽

Cited By ~ 14

Author(s):

Xiwen Li ◽

Yuning Chen ◽

Yunfeng Lai ◽

Qing Yang ◽

Hao Hu ◽

...

Keyword(s):

Chinese Medicine ◽

Traditional Chinese Medicine ◽

Medicinal Plant ◽

Pesticide Residues ◽

Large Scale ◽

Plant Disease ◽

Supply And Demand ◽

Systematic Evaluation ◽

Sustainable Utilization ◽

Market Demand

The usage amount of medicinal plant rapidly increased along with the development of traditional Chinese medicine industry. The higher market demand and the shortage of wild herbal resources enforce us to carry out large-scale introduction and cultivation. Herbal cultivation can ease current contradiction between medicinal resources supply and demand while they bring new problems such as pesticide residues and plant disease and pests. Researchers have recently placed high hopes on the application of natural fostering, a new method incorporated herbal production and diversity protecting practically, which can solve the problems brought by artificial cultivation. However no modes can solve all problems existing in current herbal production. This study evaluated different production modes including cultivation, natural fostering, and wild collection to guide the traditional Chinese medicine production for sustainable utilization of herbal resources.

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Acceptability of Traditional Chinese Medicine in Chinese People Based on 10-Year's Real World Study With Mutiple Big Data Mining

Frontiers in Public Health ◽

10.3389/fpubh.2021.811730 ◽

2022 ◽

Vol 9 ◽

Author(s):

Yan Guo ◽

Tengjiao Wang ◽

Wei Chen ◽

Ted J. Kaptchuk ◽

Xilian Li ◽

...

Keyword(s):

Data Mining ◽

Big Data ◽

Chinese Medicine ◽

Traditional Chinese Medicine ◽

Real World ◽

Large Scale ◽

Point Of View ◽

Highly Educated ◽

The Past ◽

Medical Visits

In the past decades, numerous clinical researches have been conducted to illuminate the effects of traditional Chinese medicine for better inheritance and promotion of it, which are mostly clinical trials designed from the doctor's point of view. This large-scale data mining study was conducted from real-world point of view in up to 10 years' big data sets of Traditional Chinese Medicine (TCM) in China, including both medical visits to hospital and cyberspace and contemporaneous social survey data. Finally, some important and interesting findings appear: (1) More Criticisms vs. More Visits. The intensity of criticism increased by 2.33 times over the past 10 years, while the actual number of visits increased by 2.41 times. (2) The people of younger age, highly educated and from economically developed areas have become the primary population for utilizing TCM, which is contrary to common opinions on the characteristics of TCM users. The discovery of this phenomenon indicates that TCM deserves further study on how it treats illness and maintains health.

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A Core Drug Discovery Framework from Large-Scale Literature for Cold Pathogenic Disease Treatment in Traditional Chinese Medicine

Journal of Healthcare Engineering ◽

10.1155/2021/9930543 ◽

2021 ◽

Vol 2021 ◽

pp. 1-18

Author(s):

Yun Zhang ◽

Yongguo Liu ◽

Jiajing Zhu ◽

Zhi Chen ◽

Dongxiao Li ◽

...

Keyword(s):

Drug Discovery ◽

Chinese Medicine ◽

Traditional Chinese Medicine ◽

Community Detection ◽

Large Scale ◽

Word Embedding ◽

China National Knowledge Infrastructure ◽

Corpus Construction ◽

Knowledge Infrastructure ◽

Incidence And Mortality

Cold pathogenic disease is a widespread disease in traditional Chinese medicine, which includes influenza and respiratory infection associated with high incidence and mortality. Discovering effective core drugs in Chinese medicine prescriptions for treating the disease and reducing patients’ symptoms has attracted great interest. In this paper, we explore the core drugs for curing various syndromes of cold pathogenic disease from large-scale literature. We propose a core drug discovery framework incorporating word embedding and community detection algorithms, which contains three parts: disease corpus construction, drug network generation, and core drug discovery. First, disease corpus is established by collecting and preprocessing large-scale literature about the Chinese medicine treatment of cold pathogenic disease from China National Knowledge Infrastructure. Second, we adopt the Chinese word embedding model SSP2VEC for mining the drug implication implied in the literature; then, a drug network is established by the semantic similarity among drugs. Third, the community detection method COPRA based on label propagation is adopted to reveal drug communities and identify core drugs in the drug network. We compute the community size, closeness centrality, and degree distributions of the drug network to analyse the patterns of core drugs. We acquire 4681 literature from China national knowledge infrastructure. Twelve significant drug communities are discovered, in which the top-10 drugs in every drug community are recognized as core drugs with high accuracy, and four classical prescriptions for treating different syndromes of cold pathogenic disease are discovered. The proposed framework can identify effective core drugs for curing cold pathogenic disease, and the research can help doctors to verify the compatibility laws of Chinese medicine prescriptions.

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