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

## TL;DR

This paper presents a new quantum dots-based platform for detecting rhinitis biomarkers, offering a sensitive and reliable method for rapid diagnosis.

## Contribution

A novel multiscale quantum dots-based immunosensing platform for detecting rhinitis biomarkers with high sensitivity and clinical applicability.

## Key findings

- The CQD-based immunosensor significantly improves detection sensitivity for ECP and MPO.
- The method shows strong reliability in real clinical samples and matches ELISA results in patient-derived nasal secretions.

## 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.

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