Enzyme-free catalytic hairpin assembly reaction-mediated micro-orifice resistance assay for the ultrasensitive and low-cost detection of Listeria monocytogenes.


Journal

Biosensors & bioelectronics
ISSN: 1873-4235
Titre abrégé: Biosens Bioelectron
Pays: England
ID NLM: 9001289

Informations de publication

Date de publication:
15 Oct 2022
Historique:
received: 01 04 2022
revised: 29 05 2022
accepted: 16 06 2022
pubmed: 7 7 2022
medline: 27 7 2022
entrez: 6 7 2022
Statut: ppublish

Résumé

The rapid, reliable, ultra-sensitive, and cost-saving detection of Listeria monocytogenes (L. monocytogenes) has substantial implications for food safety. Thus, we developed a novel, enzyme-free, dual-signal amplification approach to detect L. monocytogenes based on the micro-orifice resistance technique combined with the aggregation of polystyrene (PS) microspheres constructed by the catalytic hairpin assembly reaction (CHA). Both the detection probes (probe

Identifiants

pubmed: 35793606
pii: S0956-5663(22)00530-9
doi: 10.1016/j.bios.2022.114490
pii:
doi:

Substances chimiques

DNA 9007-49-2

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

114490

Informations de copyright

Copyright © 2022 Elsevier B.V. All rights reserved.

Auteurs

Liangqiong Ren (L)

College of Food Science and Technology, Huazhong Agricultural University, Wuhan, 430070, China; Shenzhen Institute of Food Nutrition and Health, Huazhong Agricultural University, Wuhan, 430070, Hubei, China.

Feng Hong (F)

College of Food Science and Technology, Huazhong Agricultural University, Wuhan, 430070, China.

Yiping Chen (Y)

College of Food Science and Technology, Huazhong Agricultural University, Wuhan, 430070, China; Guangdong Laboratory for Lingnan Modern Agriculture, Guangzhou, 510642, Guangdong, China; Hubei Hongshan Laboratory, Wuhan, 430070, China; Shenzhen Institute of Food Nutrition and Health, Huazhong Agricultural University, Wuhan, 430070, Hubei, China. Electronic address: chenyiping@mail.hzau.edu.cn.

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Classifications MeSH