A multiscale quantum dots-based material platform for high-performance immunosensing of rhinitis biomarkers

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Authors: Jingqiu Chen, Jingqiu Chen, Hegeng Li, Y. M. Tao, Wenjian Zhang, Xinyi Chen, Yunong Zhao, Lanpeng Guo, Qing Huang, Jianjun Chen, Jianjun Chen, Huan Liu
Cited by: 1
References: 27

Abstract

Rhinitis is a common chronic respiratory disease that severely affects patients' quality of life and may lead to serious complications, underscoring the need for rapid and portable diagnostic tools to support routine monitoring and clinical management. Here, we introduce a multiscale material platform based on colloidal quantum dots (CQDs) for the construction of electrochemical immunosensors enabling the rapid detection of eosinophil cationic protein (ECP) and neutrophil myeloperoxidase (MPO), two clinically relevant biomarkers of rhinitis. The platform leverages specific antigen-antibody recognition coupled with the electrical transduction properties of CQDs, resulting in significant improvement of detection sensitivity. To ensure translational applicability, we systematically examined key factors associated with real clinical samples, including hemolysis, storage duration, and preservation conditions in serum, and verified the method's reliability through spiked recovery experiments. More over, the immunosensor was successfully applied to the detection of ECP and MPO in patient-derived nasal secretion samples, exhibiting strong concordance with enzyme-linked immunosorbent assay (ELISA) results. Collectively, this work demonstrates that the CQD-based material platform offers a robust and clinically validated strategy for protein biomarker detection, and highlights its strong potential for home-based diagnostics, providing valuable support for the early diagnosis and management of rhinitis.

Fields of Study & Subjects

Biosensors and Analytical Detection Allergic Rhinitis and Sensitization Carbon and Quantum Dots Applications

Publication details

Journal / source
Materials Today Bio
Publisher
Elsevier BV
Volume
37
Pages
102839–102839
Publication date
22 January 2026
Language
EN