Evidence map›Paper›PMID 32754034›Full record

ArticleFrontiers in pharmacology2020

Uncovering the Complexity Mechanism of Different Formulas Treatment for Rheumatoid Arthritis Based on a Novel Network Pharmacology Model.

Ke-Xin Wang, Yao Gao, Cheng Lu, Yao Li, Bo-Ya Zhou, Xue-Mei Qin, Guan-Hua Du, Li Gao, Dao-Gang Guan, Ai-Ping Lu

Abstract read
In one paragraph

Article in Frontiers in pharmacology, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 29 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
29citing papers in PubMed, 1 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

29 citing papers in PubMed, 1 synthesis or guideline pooled it.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

10 authors.

Ke-Xin WangModern Research Center for Traditional Chinese Medicine, Shanxi University, Taiyuan, China.
Yao GaoModern Research Center for Traditional Chinese Medicine, Shanxi University, Taiyuan, China.
Cheng LuInstitute of Basic Research in Clinical Medicine, China Academy of Chinese Medical Sciences, Beijing, China.
Yao LiInstitute of Integrated Bioinformedicine and Translational Science, Hong Kong Baptist University, Hong Kong, Hong Kong.
Bo-Ya ZhouDepartment of Ultrasound, Eighth Affiliated Hospital of Sun Yat-sen University, Guangzhou, China.
Xue-Mei QinModern Research Center for Traditional Chinese Medicine, Shanxi University, Taiyuan, China.
Guan-Hua DuModern Research Center for Traditional Chinese Medicine, Shanxi University, Taiyuan, China.
Li GaoModern Research Center for Traditional Chinese Medicine, Shanxi University, Taiyuan, China.
Dao-Gang GuanDepartment of Biochemistry and Molecular Biology, School of Basic Medical Sciences, Southern Medical University, Guangzhou, China.
Ai-Ping LuInstitute of Integrated Bioinformedicine and Translational Science, Hong Kong Baptist University, Hong Kong, Hong Kong.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Traditional Chinese medicine (TCM) with the characteristics of "multi-component-multi-target-multi-pathway" has obvious advantages in the prevention and treatment of complex diseases, especially in the aspects of "treating the same disease with different treatments". However, there are still some problems such as unclear substance basis and molecular mechanism of the effectiveness of formula. Network pharmacology is a new strategy based on system biology and poly-pharmacology, which could observe the intervention of drugs on disease networks at systematical and comprehensive level, and especially suitable for study of complex TCM systems. Rheumatoid arthritis (RA) is a chronic inflammatory autoimmune disease, causing articular and extra articular dysfunctions among patients, it could lead to irreversible joint damage or disability if left untreated. TCM formulas, Danggui-Sini-decoction (DSD), Guizhi-Fuzi-decoction (GFD), and Huangqi-Guizhi-Wuwu-Decoction (HGWD), et al., have been found successful in controlling RA in clinical applications. Here, a network pharmacology-based approach was established. With this model, key gene network motif with significant (KNMS) of three formulas were predicted, and the molecular mechanism of different formula in the treatment of rheumatoid arthritis (RA) was inferred based on these KNMSs. The results show that the KNMSs predicted by the model kept a high consistency with the corresponding C-T network in coverage of RA pathogenic genes, coverage of functional pathways and cumulative contribution of key nodes, which confirmed the reliability and accuracy of our proposed KNMS prediction strategy. All validated KNMSs of each RA therapy-related formula were employed to decode the mechanisms of different formulas treat the same disease. Finally, the key components in KNMSs of each formula were evaluated by

Indexed as

key gene network motif with significant (KNMS)mechanismsnetwork pharmacologyrheumatoid arthritisTraditional Chinese medicine (TCM)

Identifiers

PMID32754034
PMCPMC7365894

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