Evidence map›Paper›PMID 34867400›Full record

ArticleFrontiers in pharmacology2021

Large Screening Identifies ACE2 Positively Correlates With NF-κB Signaling Activity and Targeting NF-κB Signaling Drugs Suppress ACE2 Levels.

Meichen Yan, Yuan Dong, Xuena Bo, Yong Cheng, Jinbo Cheng

Open access · goldAbstract read
In one paragraph

Article in Frontiers in pharmacology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.

0numbers the graph read from it
0cells of the map it votes in
11citing papers in PubMed
0.4field-weighted citation impact, top 36% 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

11 citing papers in PubMed, 12 citations in OpenAlex.

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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

5 authors at 2 institutions in 1 country.

Meichen YanCenter on Translational Neuroscience, College of Life and Environmental Science, Minzu University of China, Beijing, China.
Yuan DongDepartment of Biochemistry, Medical College, Qingdao University, Qingdao, China.
Xuena BoCenter on Translational Neuroscience, College of Life and Environmental Science, Minzu University of China, Beijing, China.
Yong ChengCenter on Translational Neuroscience, College of Life and Environmental Science, Minzu University of China, Beijing, China.
Jinbo ChengCenter on Translational Neuroscience, College of Life and Environmental Science, Minzu University of China, Beijing, China.
Minzu University of China · CNQingdao University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Coronaviruses SARS-CoV-2 infected more than 156 million people and caused over 3 million death in the whole world, therefore a better understanding of the underlying pathogenic mechanism and the searching for more effective treatments were urgently needed. Angiotensin-converting enzyme 2 (ACE2) was the receptor for SARS-CoV-2 infection. In this study, we found that ACE2 was an interferon-stimulated gene (ISG) in human cell lines. By performing an ISG library screening, we found that ACE2 levels were positively regulated by multiple ISGs. Interestingly, ACE2 levels were highly correlated with ISGs-induced NF-κB activities, but not IFNβ levels. Furthermore, using an approved clinical durgs library, we found two clinical drugs, Cepharanthine and Glucosamine, significantly inhibited ACE2 level, IFNβ level, and NF-κB signaling downstream TNFα and IL6 levels. Our finding suggested the possible inhibitory effects of Cepharanthine and Glucosamine during SARS-CoV-2 infection and the subsequent inflammatory cytokine storm.

Indexed as

angiotensin-converting enzyme 2clinical drugsinflammatory cytokine storminterferon-stimulated geneNF-κB signaling

Identifiers

PMID34867400
PMCPMC8639591
OpenAlexW3216392160

What OpenQuestion holds

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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.