Evidence map›Paper›PMID 32192182›Full record

ReviewMicroorganisms2020

Quorum-Sensing Regulation of Antimicrobial Resistance in Bacteria.

Xihong Zhao, Zixuan Yu, Tian Ding

Open access · goldAbstract readReview
In one paragraph

Review in Microorganisms, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 189 papers.

0numbers the graph read from it
0cells of the map it votes in
189citing papers in PubMed
20.4field-weighted citation impact, top 1% 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

189 citing papers in PubMed, 465 citations in OpenAlex.

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  18. Targeting biofilm and virulence inMicrobiology spectrum · 2026
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129 more citing papers are in PubMed but not listed here.

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

3 authors at 2 institutions in 1 country.

Xihong ZhaoResearch Center for Environmental Ecology and Engineering, Key Laboratory for Green Chemical Process of Ministry of Education, Hubei Key Laboratory of Novel Reactor and Green Chemistry Technology, School of Environmental Ecology and Biological Engineering, Wuhan Institute of Technology, Wuhan 430205, China.
Zixuan YuResearch Center for Environmental Ecology and Engineering, Key Laboratory for Green Chemical Process of Ministry of Education, Hubei Key Laboratory of Novel Reactor and Green Chemistry Technology, School of Environmental Ecology and Biological Engineering, Wuhan Institute of Technology, Wuhan 430205, China.
Tian DingCollege of Biosystems Engineering and Food Science, National-Local Joint Engineering Laboratory of Intelligent Food Technology and Equipment, Zhejiang Key Laboratory for Agro-Food Processing, Zhejiang University, Hangzhou 310058, China.
Wuhan Institute of Technology · CNZhejiang University · CN

Funding

National Natural Science Foundation of China 31501582
6 · The paper itself

Abstract

Quorum sensing is a cell-to-cell communication system that exists widely in the microbiome and is related to cell density. The high-density colony population can generate a sufficient number of small molecule signals, activate a variety of downstream cellular processes including virulence and drug resistance mechanisms, tolerate antibiotics, and harm the host. This article gives a general introduction to the current research status of microbial quorum-sensing systems, focuses on the role of quorum-sensing systems in regulating microbial resistance mechanisms, such as drug efflux pump and microbial biofilm formation regulation, and discusses a new strategy for the treatment of drug-resistant bacteria proposed by using quorum quenching to prevent microbial resistance.

Indexed as

biofilmmicrobial resistancequorum quenchingquorum sensing

Identifiers

PMID32192182
PMCPMC7143945
OpenAlexW3012106863

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.