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New microarrays Raman sensor for lung cancer biomarker detection

Date: 11-15-2019   source:    Print

Volatile organic compounds (VOCs) have been recognized as a significant endogenous signaling molecule in human exhalation and are closely associated with a number of pathophysiological processes. The profile of VOCs differs between patients with lung cancer and healthy subjects. The detection of trace VOCs in breath sampling is completely noninvasive and constitutes a potentially useful approach to screening lung cancer.
Recently, Professor WANG Tie from Institute of Chemistry, Chinese Academy of Sciences (ICCAS) designed and developed a new microarrays Raman sensor for cancer biomarker detection, where the bunched Co-Ni layered double hydroxide nanocages coated on Ag nanowire (Ag@LDH) by ion etching of zeolitic imidazolate framework on silver nanowires (Ag@ZIF-67). The nanocage structure exhibited excellent gas absorption performance and the targeted analytes were more efficiently reacted or absorbed on the SERS active site, which was verified from gas hydrodynamics. Consequently, the detection limit of Ag@LDH SERS sensors for biomarker was an order of magnitude lower than that of Ag@ZIF-67, and three orders of magnitude lower than that of bare Ag nanowires. Various aldehydes in mixed mimetic gas were distinguished by Raman spectra statistical analysis assisted by multivariate methods. The detection information was recorded in a barcode, which can be used for the design and development of a desktop SERS sensor analysis system for large-scale lung cancer detection.
The work entitled “Detection of Exhaled Volatile Organic Compounds Improved by Hollow Nanocages of Layered Double Hydroxide on Ag Nanowries” was published in Angew. Chem. Int. Ed.2019, DOI: 10.1002/ange.201910865.

Illustration of principle of microarrays Raman sensor and enhanced gas molecular adsorption mechanism. (Image by Prof. WANG Tie)

 

Contact:
Prof. WANG Tie
Institute of Chemistry, Chinese Academy of Sciences
Tel: 86-10-82362042
E-mail: wangtie@iccas.ac.cn

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