Enhanced biosensing of tumor necrosis factor-alpha based on aptamer-functionalized surface plasmon resonance substrate and Goos-Hänchen shift.


Journal

The Analyst
ISSN: 1364-5528
Titre abrégé: Analyst
Pays: England
ID NLM: 0372652

Informations de publication

Date de publication:
12 Apr 2024
Historique:
medline: 12 4 2024
pubmed: 12 4 2024
entrez: 12 4 2024
Statut: aheadofprint

Résumé

Tumor necrosis factor-alpha (TNF-α) serves as a crucial biomarker in various diseases, necessitating sensitive detection methodologies. This study introduces an innovative approach utilizing an aptamer-functionalized surface plasmon resonance (SPR) substrate together with an ultrasensitive measure, the Goos-Hänchen (GH) shift, to achieve sensitive detection of TNF-α. The developed GH-aptasensing platform has shown a commendable figure-of-merit of 1.5 × 10

Identifiants

pubmed: 38606503
doi: 10.1039/d4an00194j
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Auteurs

Kathrine Nygaard Borg (KN)

Department of Biomedical Engineering, The Chinese University of Hong Kong, Shatin, Hong Kong SAR, China. ypho@cuhk.edu.hk.
Light, Nanomaterials & Nanotechnologies (L2n), CNRS-UMR 7076, University of Technology of Troyes, 10000, Troyes, France. shuwen.zeng@cnrs.fr.

Rodolphe Jaffiol (R)

Light, Nanomaterials & Nanotechnologies (L2n), CNRS-UMR 7076, University of Technology of Troyes, 10000, Troyes, France. shuwen.zeng@cnrs.fr.

Yi-Ping Ho (YP)

Department of Biomedical Engineering, The Chinese University of Hong Kong, Shatin, Hong Kong SAR, China. ypho@cuhk.edu.hk.
Centre for Biomaterials, The Chinese University of Hong Kong, Hong Kong SAR, China.
Hong Kong Branch of CAS Center for Excellence in Animal Evolution and Genetics, Hong Kong SAR, China.
State Key Laboratory of Marine Pollution, City University of Hong Kong, Hong Kong SAR, China.

Shuwen Zeng (S)

Light, Nanomaterials & Nanotechnologies (L2n), CNRS-UMR 7076, University of Technology of Troyes, 10000, Troyes, France. shuwen.zeng@cnrs.fr.

Classifications MeSH