Quick Navigation
Topics
Spin Qubits Silicon Quantum Computing
Development of a DMSNs@CuInS/ZnS-based flow immunochromatographic strip method for gliadin detection.
PubMed
Authors: Sheng L, Liu X, Zhang Y, Xie N, Lu Y
Year
2026
Paper ID
642
Status
Peer-reviewed
Abstract Read
~2 min
Abstract Words
146
Citations
N/A
Abstract
In this study, we developed a fluorescent lateral flow immunoassay (LFIA) using CuInS/ZnS quantum dots loaded onto dendritic mesoporous silica nanoparticles (DMSNs) as the signal reporter for the rapid and sensitive detection of gliadin. We enhanced signal amplification by loading CuInS/ZnS quantum dots within DMSNs. Under systematically optimized conditions, the established method exhibited a wide linear range from 12.50 ± 0.47 μg/L to 1200.00 ± 1.69 μg/L, with an exceptionally low limit of detection (LOD) of 0.02 ± 0.01 μg/L. During the analysis of real food samples, the spiked recovery rates for biscuit, bread, and flour samples were 82.19 %-111.50 %, 96.73 %-109.45 %, and 89.26 %-116.57 %, respectively. Our results were validated using a commercial enzyme-linked immunosorbent assay (ELISA) kit, validating the high accuracy and practical applicability of our method for monitoring gluten in food samples. These results demonstrated that our proposed LFIA-based approach could be used as a reliable tool for gluten allergy management.
Why This Paper Matters
- This paper contributes to the Spin Qubits & Silicon Quantum Computing research area in the Quantum Articles archive.
- It adds a 2026 reference point for readers tracking recent quantum research.
- In this study, we developed a fluorescent lateral flow immunoassay (LFIA) using CuInS/ZnS quantum dots loaded onto dendritic mesoporous silica nanoparticles (DMSNs) as the...
Paper Tools
Become a member to use research tools
Sign in to open papers, visit source links, share, cite, compare, copy DOI links, request category corrections, and build your reading list.
Show Paper Publisher Share
Cite This Paper
Copy URL
Compare
Copy DOI Add to Reading List
Category Correction Request
Category Correction Request
Help us improve classification quality by proposing a better category. Every request is reviewed by an admin.
Sign in to submit a category correction request for this paper.
Log In to SubmitReferences & Citation Signals
Community Reactions
Quick sentiment from readers on this paper.
Score:
0
Likes: 0
Dislikes: 0
Sign in to react to this paper.
Discussion & Reviews (Moderated)
Average Rating: 0.0 / 5 (0 ratings)
No written reviews yet.