Evidence map›Paper›PMID 38896257›Full record

ReviewApplied microbiology and biotechnology2024

Application of biofilm dispersion-based nanoparticles in cutting off reinfection.

Xiaojuan Li, Shiyu Lin, Yueli Wang, Yang Chen, Wei Zhang, Gang Shu, Haohuan Li, Funeng Xu, Juchun Lin, Guangneng Peng and 1 more

Abstract readReview
In one paragraph

Review in Applied microbiology and biotechnology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. 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

11 authors.

Xiaojuan LiInnovative Engineering Research Center of Veterinary Pharmaceutics, Department of Pharmacy, College of Veterinary Medicine, Sichuan Agricultural University, Chengdu, 611130, Sichuan, China.
Shiyu LinInnovative Engineering Research Center of Veterinary Pharmaceutics, Department of Pharmacy, College of Veterinary Medicine, Sichuan Agricultural University, Chengdu, 611130, Sichuan, China.
Yueli WangInnovative Engineering Research Center of Veterinary Pharmaceutics, Department of Pharmacy, College of Veterinary Medicine, Sichuan Agricultural University, Chengdu, 611130, Sichuan, China.
Yang ChenInnovative Engineering Research Center of Veterinary Pharmaceutics, Department of Pharmacy, College of Veterinary Medicine, Sichuan Agricultural University, Chengdu, 611130, Sichuan, China.
Wei ZhangInnovative Engineering Research Center of Veterinary Pharmaceutics, Department of Pharmacy, College of Veterinary Medicine, Sichuan Agricultural University, Chengdu, 611130, Sichuan, China.
Gang ShuInnovative Engineering Research Center of Veterinary Pharmaceutics, Department of Pharmacy, College of Veterinary Medicine, Sichuan Agricultural University, Chengdu, 611130, Sichuan, China.
Haohuan LiInnovative Engineering Research Center of Veterinary Pharmaceutics, Department of Pharmacy, College of Veterinary Medicine, Sichuan Agricultural University, Chengdu, 611130, Sichuan, China.
Funeng XuInnovative Engineering Research Center of Veterinary Pharmaceutics, Department of Pharmacy, College of Veterinary Medicine, Sichuan Agricultural University, Chengdu, 611130, Sichuan, China.
Juchun LinInnovative Engineering Research Center of Veterinary Pharmaceutics, Department of Pharmacy, College of Veterinary Medicine, Sichuan Agricultural University, Chengdu, 611130, Sichuan, China.
Guangneng PengInnovative Engineering Research Center of Veterinary Pharmaceutics, Department of Pharmacy, College of Veterinary Medicine, Sichuan Agricultural University, Chengdu, 611130, Sichuan, China.
Hualin FuInnovative Engineering Research Center of Veterinary Pharmaceutics, Department of Pharmacy, College of Veterinary Medicine, Sichuan Agricultural University, Chengdu, 611130, Sichuan, China. fuhl2005@sohu.com.ORCID http://orcid.org/0000-0002-6215-8968

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Bacterial biofilms commonly cause chronic and persistent infections in humans. Bacterial biofilms consist of an inner layer of bacteria and an autocrine extracellular polymeric substance (EPS). Biofilm dispersants (abbreviated as dispersants) have proven effective in removing the bacterial physical protection barrier EPS. Dispersants are generally weak or have no bactericidal effect. Bacteria dispersed from within biofilms (abbreviated as dispersed bacteria) may be more invasive, adhesive, and motile than planktonic bacteria, characteristics that increase the probability that dispersed bacteria will recolonize and cause reinfection. The dispersants should be combined with antimicrobials to avoid the risk of severe reinfection. Dispersant-based nanoparticles have the advantage of specific release and intense penetration, providing the prerequisite for further antibacterial agent efficacy and achieving the eradication of biofilms. Dispersant-based nanoparticles delivered antimicrobial agents for the treatment of diseases associated with bacterial biofilm infections are expected to be an effective measure to prevent reinfection caused by dispersed bacteria. KEY POINTS: • Dispersed bacteria harm and the dispersant's dispersion mechanisms are discussed. • The advantages of dispersant-based nanoparticles in bacteria biofilms are discussed. • Dispersant-based nanoparticles for cutting off reinfection in vivo are highlighted.

Indexed as

Anti-Bacterial AgentsBiofilmsNanoparticlesBacteriaBacterial InfectionsExtracellular Polymeric Substance MatrixHumansReinfectionAnti-Bacterial AgentsBacterial biofilmBiofilm dispersantsDispersant-based nanoparticlesDispersed bacteria

Identifiers

PMID38896257
PMCPMC11186951

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.