Evidence map›Paper›PMID 35590353›Full record

ArticleBMC complementary medicine and therapies2022

The potential effects and mechanisms of hispidulin in the treatment of diabetic retinopathy based on network pharmacology.

Yao Chen, Jiaojiao Sun, Zhiyun Zhang, Xiaotong Liu, Qiaozhi Wang, Yang Yu

Erratum issuedOpen access · goldAbstract read
In one paragraph

Article in BMC complementary medicine and therapies, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed
2.3field-weighted citation impact, top 11% 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

8 citing papers in PubMed, 16 citations in OpenAlex.

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4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

6 authors at 2 institutions in 1 country.

Yao ChenDepartment of Histology Anatomy and HistoEmbryology, School of Basic Medical Sciences, Southwest Medical University, Luzhou, Sichuan, 646000, P.R. China.
Jiaojiao SunDepartment of Histology Anatomy and HistoEmbryology, School of Basic Medical Sciences, Southwest Medical University, Luzhou, Sichuan, 646000, P.R. China.
Zhiyun ZhangDepartment of Clinical Medicine, School of Clinical Medicine, Southwest Medical University, Luzhou, Sichuan, 646000, P.R. China.
Xiaotong LiuJiangyang City Construction College, Luzhou, Sichuan, 646000, P.R. China.
Qiaozhi WangDepartment of Histology Anatomy and HistoEmbryology, School of Basic Medical Sciences, Southwest Medical University, Luzhou, Sichuan, 646000, P.R. China. Wqz416@163.com.
Yang YuDepartment of Histology Anatomy and HistoEmbryology, School of Basic Medical Sciences, Southwest Medical University, Luzhou, Sichuan, 646000, P.R. China. yuyang80@swmu.edu.cn.
Southwest Medical University · CNMinistry of Education of the People's Republic of China · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundDiabetic retinopathy (DR), one of the most common and severe microvascular complication of diabetes mellitus (DM), is mainly caused by diabetic metabolic disorder. So far, there is no effective treatment for DR. Eriocauli Flos, a traditional Chinese herb, has been used in treating the ophthalmic diseases including DR. However, the active ingredients and molecular mechanisms of Eriocauli Flos to treat diabetic retinopathy remain elusive.

methodsHere, the systems pharmacology model was developed via constructing network approach. 8 active components which were screened by oral bioavailability (OB ≥ 30%) and drug-likeness (DL ≥ 0.18) and 154 targets were selected from Eriocauli Flos through TCMSP database. Another 3593 targets related to DR were obtained from Genecards, OMIM, TTD, and Drugbank databases. The 103 intersecting targets of DR and Eriocauli Flos were obtained by Draw Venn Diagram. In addition, protein-protein interaction network was established from STRING database and the compound-target network was constructed by Cytoscape which screened top 12 core targets with cytoNCA module. Then the overlapping targets were analyzed by GO and KEGG enrichment. Moreover, two core targets were selected to perform molecular docking simulation. Subsequently, CCK8 assay, RT-PCR and Western blotting were applied to further reveal the mechanism of new candidate active component from Eriocauli Flos in high glucose-induced HRECs.

resultsThe results showed that the overlapping targets by GO analysis were enriched in cellular response to chemical stress, response to oxidative stress, response to reactive oxygen species, reactive oxygen species metabolic process and so on. Besides, the overlapping targets principally regulated pathways such as AGE-RAGE signaling pathway in diabetic complications, lipid atherosclerosis, fluid shear stress and atherosclerosis, and PI3K-Akt signaling pathway. Molecular docking exhibited that VEGFA and TNF-α, had good bindings to the great majority of compounds, especially the compound hispidulin. In vitro, hispidulin ameliorated high-glucose induced proliferation by down-regulating the expression of p-ERK, p-Akt, and VEGFA; meanwhile inhibited the mRNA levels of TNF-α.

conclusionsIn this study, through network pharmacology analysis and experimental validation, we found that hispidulin maybe has a potential targeted therapy effect for DR by decreasing the expression of p-Akt, p-ERK, and VEGFA, which resulted in ameliorating the proliferation in HRECs.

Indexed as

AtherosclerosisDiabetes MellitusDiabetic RetinopathyDrugs, Chinese HerbalFlavonesGlucoseHumansMolecular Docking SimulationNetwork PharmacologyPhosphatidylinositol 3-KinasesProto-Oncogene Proteins c-aktTumor Necrosis Factor-alphaDrugs, Chinese HerbalFlavonesGlucosehispidulinPhosphatidylinositol 3-KinasesProto-Oncogene Proteins c-aktTumor Necrosis Factor-alphaDiabetic retinopathyEriocauli FlosHispidulinMolecular dockingNetwork pharmacology

Identifiers

PMID35590353
PMCPMC9121581
OpenAlexW4280624446

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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.