Evidence map›Paper›PMID 28272527›Full record

ArticleScientific reports2017

A network-based method for mechanistic investigation of Shexiang Baoxin Pill's treatment of cardiovascular diseases.

Hai-Yang Fang, Hua-Wu Zeng, Li-Mei Lin, Xing Chen, Xiao-Na Shen, Peng Fu, Chao Lv, Qun Liu, Run-Hui Liu, Wei-Dong Zhang and 1 more

Abstract read
In one paragraph

Article in Scientific reports, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 46 papers, 3 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
46citing papers in PubMed, 3 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

46 citing papers in PubMed, 3 syntheses or guidelines 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

11 authors.

Hai-Yang FangDepartment of Mathematics, Logistical Engineering University, Chongqing, China.
Hua-Wu ZengDepartment of Natural Medicinal Chemistry, Second Military Medical University, Shanghai, China.
Li-Mei LinDepartment of Mathematics, Logistical Engineering University, Chongqing, China.
Xing ChenDepartment of Mathematics, Logistical Engineering University, Chongqing, China.
Xiao-Na ShenDepartment of Mathematics, Logistical Engineering University, Chongqing, China.
Peng FuDepartment of Natural Medicinal Chemistry, Second Military Medical University, Shanghai, China.
Chao LvDepartment of Natural Medicinal Chemistry, Second Military Medical University, Shanghai, China.
Qun LiuDepartment of Natural Medicinal Chemistry, Second Military Medical University, Shanghai, China.
Run-Hui LiuDepartment of Natural Medicinal Chemistry, Second Military Medical University, Shanghai, China.
Wei-Dong ZhangDepartment of Natural Medicinal Chemistry, Second Military Medical University, Shanghai, China.
Jing ZhaoDepartment of Mathematics, Logistical Engineering University, Chongqing, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Shexiang Baoxin Pill (SBP), a traditional Chinese medicine formula, is commonly used to treat cardiovascular disease (CVD) in China. However, the complexity of composition and targets has deterred our understanding of its mechanism of action. Using network pharmacology-based approaches, we established the mechanism of action for SBP to treat CVD by analyzing protein-protein interactions and pathways. The computational results were confirmed at the gene expression level in microarray-based studies. Two of the SBP's targets were further confirmed at the protein level by Western blot. In addition, we validated the theory that SBP's plasma absorbed compounds play major therapeutic role in treating CVD.

Indexed as

Signal TransductionCardiovascular DiseasesCell LineDrugs, Chinese HerbalGene Expression RegulationGene Regulatory NetworksHumansProtein Interaction MappingProtein Interaction MapsReproducibility of ResultsDrugs, Chinese Herbalshexiang baoxin

Identifiers

PMID28272527
PMCPMC5341564

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Registered trials

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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.