One‐droplet saliva detection on photonic crystal‐based competitive immunoassay for precise diagnosis of migraine
Xiaoxue Lin,
Jimei Chi,
Zewei Lian,
Yang Yun,
Xu Yang,
Xuwei He,
Zheng Liu,
Shuqing Wang,
Wei Zhao,
Zihua Gong,
Yingyuan Liu,
Shuhua Zhang,
Deqi Zhai,
Siyuan Xie,
Yin Sun,
Meng Su,
Zhao Dong,
Shengyuan Yu,
Yanlin Song
Affiliations
Xiaoxue Lin
Chinese PLA Medical School Beijing China
Jimei Chi
Key Laboratory of Green Printing, Beijing National Laboratory for Molecular Sciences (BNLMS) Institute of Chemistry, Chinese Academy of Sciences (ICCAS)/Beijing Engineering Research Center of Nanomaterials for Green Printing Technology Beijing China
Zewei Lian
Key Laboratory of Green Printing, Beijing National Laboratory for Molecular Sciences (BNLMS) Institute of Chemistry, Chinese Academy of Sciences (ICCAS)/Beijing Engineering Research Center of Nanomaterials for Green Printing Technology Beijing China
Yang Yun
Key Laboratory of Green Printing, Beijing National Laboratory for Molecular Sciences (BNLMS) Institute of Chemistry, Chinese Academy of Sciences (ICCAS)/Beijing Engineering Research Center of Nanomaterials for Green Printing Technology Beijing China
Xu Yang
Key Laboratory of Green Printing, Beijing National Laboratory for Molecular Sciences (BNLMS) Institute of Chemistry, Chinese Academy of Sciences (ICCAS)/Beijing Engineering Research Center of Nanomaterials for Green Printing Technology Beijing China
Xuwei He
Chinese PLA Medical School Beijing China
Zheng Liu
Chinese PLA Medical School Beijing China
Shuqing Wang
Chinese PLA Medical School Beijing China
Wei Zhao
Chinese PLA Medical School Beijing China
Zihua Gong
Chinese PLA Medical School Beijing China
Yingyuan Liu
Chinese PLA Medical School Beijing China
Shuhua Zhang
Department of Neurology School of Medicine, Nankai University Tianjin China
Deqi Zhai
Chinese PLA Medical School Beijing China
Siyuan Xie
Department of Neurology School of Medicine, Nankai University Tianjin China
Yin Sun
Chinese PLA Medical School Beijing China
Meng Su
Key Laboratory of Green Printing, Beijing National Laboratory for Molecular Sciences (BNLMS) Institute of Chemistry, Chinese Academy of Sciences (ICCAS)/Beijing Engineering Research Center of Nanomaterials for Green Printing Technology Beijing China
Zhao Dong
Department of Neurology The First Medical Center, Chinese PLA General Hospital Beijing China
Shengyuan Yu
Department of Neurology The First Medical Center, Chinese PLA General Hospital Beijing China
Yanlin Song
Key Laboratory of Green Printing, Beijing National Laboratory for Molecular Sciences (BNLMS) Institute of Chemistry, Chinese Academy of Sciences (ICCAS)/Beijing Engineering Research Center of Nanomaterials for Green Printing Technology Beijing China
Abstract Migraine exhibits a substantial prevalence worldwide. The current diagnostic criteria rests exclusively on clinical characteristics without any objective and reliable means. The calcitonin gene‐related peptide (CGRP), as a biomarker for distinguishing migraine, undergoes swift degradation, featuring a half‐life of under 10 min, which poses a significant challenge to the point‐of‐care testing of CGRP in clinical application. Here, a photonic crystal (PC)‐based biochip has been developed to detect CGRP via the fluorescence competition assay. The chip integrates the functionalities of fluorescence enhancement and hydrophilic–hydrophobic patterning enrichment, enabling rapid and sensitive detection of CGRP. After investigating the optimal enhancement distance of fluorescence near PCs, the chip allows CGRP detection using <30 μL of saliva at room temperature within 10 min. A minimum detection limit of 0.05 pg/mL is achieved. Furthermore, CGRP concentrations in the saliva of 70 subjects have been tested by PC biochips. The results exhibit strong concordance with the enzyme‐linked immunosorbent assay (ELISA), demonstrating a linear correlation coefficient of R2 of 0.97. This sensitive detection of markers within such a short duration surpasses the capacities of ELISA, which paves the way for establishing a precise diagnostic framework integrating clinical phenotypes and biomarkers for migraine.
