Evidence map›Paper›PMID 36213575›Full record

ArticleComputational and mathematical methods in medicine2022

Cardioprotective Mechanism and Active Compounds of

Xue Sun, Yiming Zhu, Fang Li, Min Li, Guoxing Wan

Open access · hybridAbstract read
In one paragraph

Article in Computational and mathematical methods in medicine, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
1.2field-weighted citation impact, top 18% 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

2 citing papers in PubMed, 4 citations in OpenAlex.

  1. Review
  2. 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 at 1 institution in 1 country.

Xue SunDepartment of Oncology, Renmin Hospital, Hubei University of Medicine, 39# Chaoyang Road, Shiyan, Hubei 442000, China.ORCID https://orcid.org/0000-0003-2909-7304
Yiming ZhuDepartment of Oncology, Renmin Hospital, Hubei University of Medicine, 39# Chaoyang Road, Shiyan, Hubei 442000, China.ORCID https://orcid.org/0000-0002-2724-959X
Fang LiDepartment of Oncology, Renmin Hospital, Hubei University of Medicine, 39# Chaoyang Road, Shiyan, Hubei 442000, China.ORCID https://orcid.org/0000-0002-0647-0834
Min LiDepartment of Oncology, Renmin Hospital, Hubei University of Medicine, 39# Chaoyang Road, Shiyan, Hubei 442000, China.ORCID https://orcid.org/0000-0003-4551-9909
Guoxing WanDepartment of Oncology, Renmin Hospital, Hubei University of Medicine, 39# Chaoyang Road, Shiyan, Hubei 442000, China.ORCID https://orcid.org/0000-0002-0681-0456
Hubei University of Medicine · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Objective: To investigate the mechanism of Methods: Active ingredients of FG were screened by TCMSP, and the targets of active ingredient were collected by Genclip3 and HERB databases. AIC-related target genes were predicted by Genecards, OMIM, and CTD databases. Protein-protein interaction (PPI) network was constructed by STRING platform and imported into Cytoscape software to construct the FG-active ingredients-targets-AIC network, and CytoNCA plug-in was used to analyze and identify the core target genes. The Metascape platform was used for transcription factor, GO and signaling pathway enrichment analysis. Results: 27 active ingredients of FG and 1846 potential targets were obtained and 358 AIC target genes were retrieved. The intersection of FG and AIC targets resulted in 218 target genes involved in FG action. The top 5 active ingredients with most targets were quercetin, luteolin, kaempferol, isorhamnetin, and sesamin. After constructing the FG-active ingredients-targets-AIC network, CytoNCA analysis yielded 51 core targets, of which the top ranked target was STAT3. Ninety important transcription factors were enriched by transcription factor enrichment analysis, including RELA, TP53, NFKB1, SP1, JUN, STAT3, etc. The results of GO enrichment analysis showed that the effective active ingredient targets of FG were involved in apoptotic signaling, response to growth factor, cellular response to chemical stress, reactive oxygen species metabolic process, etc. The signaling pathway enrichment analysis showed that there were many signaling pathways involved in AIC, mainly including pathways in cancer, FOXO signaling pathway, AGE-RAGE signaling pathway in diabetic complications, signaling by interleukins, and PI3K-AKT signaling pathway,. Conclusions: The study based on a network pharmacology approach demonstrates that the possible mechanisms of FG against AIC are the involvement of multicomponents, multitargets, and multipathways, and STAT3 may be a key target. Further experiments are needed to verify the results.

Indexed as

Drugs, Chinese HerbalMedicine, Chinese TraditionalDoxorubicinGinkgo bilobaHumansKaempferolsLuteolinMolecular Docking SimulationNetwork PharmacologyPhosphatidylinositol 3-KinasesProto-Oncogene Proteins c-aktQuercetinReactive Oxygen SpeciesTranscription FactorsDoxorubicinDrugs, Chinese HerbalKaempferolsLuteolinPhosphatidylinositol 3-KinasesProto-Oncogene Proteins c-aktQuercetinReactive Oxygen SpeciesTranscription Factors

Identifiers

PMID36213575
PMCPMC9534669
OpenAlexW4297453861

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.