Evidence map›Paper›PMID 29731604›Full record

ArticleDrug design, development and therapy2018

A network pharmacology approach to determine the synergetic mechanisms of herb couple for treating rheumatic arthritis.

Xi-Xi Xu, Jian-Ping Bi, Li Ping, Ping Li, Fei Li

Abstract read
In one paragraph

Article in Drug design, development and therapy, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 26 papers.

0numbers the graph read from it
0cells of the map it votes in
26citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

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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

26 citing papers in PubMed.

  1. Article
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  7. The effect ofTranslational andrology and urology · 2024
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  15. Exploring the Mechanism ofEvidence-based complementary and alternative medicine : eCAM · 2021
    Article
  16. Observational
  17. Article
  18. Article
  19. Chinese Medicine for Psoriasis Vulgaris Based on Syndrome Pattern: A Network Pharmacological Study.Evidence-based complementary and alternative medicine : eCAM · 2020
    Article
  20. A Network Pharmacology Approach to Explore the Mechanisms of Shugan Jianpi Formula in Liver Fibrosis.Evidence-based complementary and alternative medicine : eCAM · 2020
    Article
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

5 authors.

Xi-Xi XuState Key Laboratory of Natural Medicines, China Pharmaceutical University, Nanjing, People's Republic of China.
Jian-Ping BiOrthopedics Department, Shandong Provincial Traditional Chinese Medical Hospital, Affiliated Hospital of Shandong University of Traditional Chinese Medicine, Jinan, People's Republic of China.
Li PingCenter for Drug Safety Evaluation and Research, Zhejiang University, Hangzhou, People's Republic of China.
Ping LiState Key Laboratory of Natural Medicines, China Pharmaceutical University, Nanjing, People's Republic of China.
Fei LiState Key Laboratory of Natural Medicines, China Pharmaceutical University, Nanjing, People's Republic of China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

purposeThe purpose of this study was to investigate the therapeutic mechanism(s) of

methodsA network pharmacology approach integrating prediction of ingredients, target exploration, network construction, module partition and pathway analysis was used.

resultsThis approach successfully helped to identify 12 active ingredients of CN, interacting with 13 key targets (Akt1, STAT3, TNFsf13, TP53, EPHB2, IL-10, IL-6, TNF, MAPK8, IL-8, RELA, ROS1 and STAT4). Kyoto Encyclopedia of Genes and Genomes pathway enrichment analysis indicated that CN-regulated pathways were mainly classified into signal transduction and immune system.

conclusionThe present work may help to illustrate the mechanism(s) of action of CN, and it may provide a better understanding of antirheumatic effects.

Indexed as

Antirheumatic AgentsDrugs, Chinese HerbalHumansMedicine, Chinese TraditionalMolecular ConformationRheumatic FeverAntirheumatic AgentsDrugs, Chinese Herbalaction mechanismClematis chinensis OsbeckNotopterygium incisum K.C. Ting ex H.T. Changpathways analysistargets prediction

Identifiers

PMID29731604
PMCPMC5923250

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.