Evidence map›Paper›PMID 29564801›Full record

ArticleChinese journal of integrative medicine2019

Bioinformatics Based Therapeutic Effects of Sinomenium Acutum.

Yu-Yan Li, Guang Zheng, Liang Liu

Abstract read
PubMed Publisher
In one paragraph

Article in Chinese journal of integrative medicine, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
0.2field-weighted citation impact, top 45% of its field
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

1 citing paper in PubMed, 4 citations in OpenAlex.

  1. 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

3 authors at 2 institutions in 2 countries.

Yu-Yan LiFaculty of Chinese Medicine, Macau University of Science and Technology, Macau, 999078, China.
Guang ZhengSchool of Information Science and Engineering, Lanzhou University, Lanzhou, 730000, China.
Liang LiuFaculty of Chinese Medicine, Macau University of Science and Technology, Macau, 999078, China. liu@must.edu.mo.
Macau University of Science and Technology · MOLanzhou University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectiveTo decipher the possible mechanisms of Sinomenium Acutum (SA) in treating diseases by a bioinformatics method.

methodsSA ingredients were searched according to Chinese Pharmacopoeia, Chinese Medicine Dictionary and Traditional Chinese Medicines Database (TCMD). Active compounds and target proteins of SA were acquired through the Pubchem platform. Pathway, network and function analyses of SA were performed with ingenuity pathway analysis (IPA), a bioinformatics analysis platform. Disease, biofunction-target networks were established with Cytoscape.

resultsEighteen ingredients from SA were obtained. Seven active ingredients with 31 active target proteins were acquired according to PubChem Bioassay test. By IPA analysis, 277 canonical pathways belonging to 17 function categories were collected, 23 kinds of diseases, 21 categories bio-functions were obtained. Based on P value, calculated by IPA, the top 5 significant pathway of SA targets include phosphatidylinositol 3 kinase/Akt (PI3K/Akt) signaling, prostate cancer signaling, macrophage migration inhibitory factor (MIF) regulation of innate immunity, Guanosine-binding protein coupled receptor (GPCR) signaling, and ataxia telangiectasia mutated protein (ATM) signaling. Disease and bio-function network analysis indicated that mitogen activated protein kinase 1 (MAPK1), MAPK3, p65 nuclear factor κB (RELA), nuclear factor of κB inhibitor alpha (NFκBIA), interleukin 1β(IL-1β), prostaglandin G/H synthase 2 (PTGS2) and tumor protein 53 (TP53) were the critical targets in various diseases treated by SA.

conclusionIn the different view of target, pathway, disease and bio-function, inflammation was found to be a central theme in many chronic conditions. SA could be used not only as an anti-inflammatory agent, but also for the treatment of cancers, neurological diseases, psychological disorders and metabolic diseases.

Indexed as

Computational BiologyDiseaseHumansMolecular Targeted TherapyProteinsSignal TransductionSinomeniumProteinsbioinformatics analysisingenuity pathway analysisnetwork pharmacologySinomenium Acutum

Identifiers

PMID29564801
OpenAlexW2793604786

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

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.