Evidence map›Paper›PMID 34580601›Full record

ArticleDisease markers2021

Network Pharmacology Reveals That Resveratrol Can Alleviate COVID-19-Related Hyperinflammation.

Zijian Xiao, Qing Ye, Xiaomei Duan, Tao Xiang

Abstract read
In one paragraph

Article in Disease markers, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers.

0numbers the graph read from it
0cells of the map it votes in
16citing papers in PubMed
–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

16 citing papers in PubMed.

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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

4 authors.

Zijian XiaoThe First Affiliated Hospital, Department of Neurology, Hengyang Medical School, University of South China, Hengyang, Hunan, China.
Qing YeThe First Affiliated Hospital, Department of Neurology, Hengyang Medical School, University of South China, Hengyang, Hunan, China.
Xiaomei DuanThe First Affiliated Hospital, Department of Neurology, Hengyang Medical School, University of South China, Hengyang, Hunan, China.
Tao XiangThe First Affiliated Hospital, Department of Neurology, Hengyang Medical School, University of South China, Hengyang, Hunan, China.ORCID https://orcid.org/0000-0002-9108-0952

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Hyperinflammation is related to the development of COVID-19. Resveratrol is considered an anti-inflammatory and antiviral agent. Herein, we used a network pharmacological approach and bioinformatic gene analysis to explore the pharmacological mechanism of Resveratrol in COVID-19 therapy. Potential targets of Resveratrol were obtained from public databases. SARS-CoV-2 differentially expressed genes (DEGs) were screened out via bioinformatic analysis Gene Expression Omnibus (GEO) datasets GSE147507, followed by Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis; then, protein-protein interaction network was constructed. The common targets, GO terms, and KEGG pathways of Resveratrol targets and SARS-CoV-2 DEGs were confirmed. KEGG Mapper queried the location of common targets in the key pathways. A notable overlap of the GO terms and KEGG pathways between Resveratrol targets and SARS-CoV-2 DEGs was revealed. The shared targets between Resveratrol targets and SARS-CoV-2 mainly involved the IL-17 signaling pathway, NF-kappa B signaling pathway, and TNF signaling pathway. Our study uncovered that Resveratrol is a promising therapeutic candidate for COVID-19 and we also revealed the probable key targets and pathways involved. Ultimately, we bring forward new insights and encourage more studies on Resveratol to benefit COVID-19 patients.

Indexed as

Anti-Inflammatory AgentsCOVID-19Gene OntologyGenes, ViralHumansInflammationMolecular Docking SimulationProtein Interaction MapsResveratrolSARS-CoV-2Anti-Inflammatory AgentsResveratrol

Identifiers

PMID34580601
PMCPMC8463930

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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.