Identification and Detection of Volatile Aldehydes as Lung Cancer Biomarkers by Vapor Generation Combined with Paper-Based Thin-Film Microextraction.

Accurate, sensitive, and selective on-spot screening of volatile aldehydes as lung cancer biomarkers is of vital significance for preclinical diagnosis and treatment guidance of cancers. However, the common methods of sensing biomarkers are limited by the fact that they are time-consuming, require professional personnel, and have complex matrixes. Here, we developed a smart vapor generation paper-based thin-film microextraction system capable of both sensitive on-field fluorescence detection and accurate surface-enhanced Raman spectroscopy (SERS) quantification of volatile benzaldehyde (BA) by utilizing stimuli-responsive core-shell gold nanorod (GNR) quantum dot (QD)-embedded metal-organic framework (MOF) structures. The amino-modified GNRs and carboxyl-capped QDs can directly assemble with each other by electrostatic interaction, which leads to an almost complete emission quenching of QDs. The addition of BA molecules destroys the GNRs-QD assemblies due to the Schiff base reactions between the amine group of 4-mercaptonoaniline and the aldehyde moiety of BA, resulting in the increase of the fluorescence and Raman signal of hybrid systems, which enables the visualization of BA with the naked eye. Moreover, the "cavity-diffusion" effect of porous MOF shells validates the selective concentration of gaseous BA molecules on the GNR surface, allowing the discrimination of BA in exhaled breath rapidly and precisely even at the sub-ppb level with excellent specificity against other volatile organic compounds. This study not only offers a versatile sensing platform for accurate discrimination of lung cancer from controls but also opens an avenue for the design of smart sensors for point-of-care applications.

A dual-responsive nanozyme sensor with ultra-high sensitivity and ultra-low cross-interference towards metabolic biomarker monitoring.

Accurate, sensitive and selective detection of metabolic biomarkers in biofluids are of vital significance for health self-monitoring and chronic disease prevention. Here, for the first time, a smart dual-responsive nanozyme sensor (DNS) was developed for simultaneous analysis of glucose and caffeine utilizing stimuli-responsive yolk-shell gold nanoparticles (GNPs)-embedded MIL-53 (Al) (GNPs@MIL-53) structures. After the introduction of glucose, GNPs@MIL-53 displays excellent glucose oxidase (GOx)-like activity to induce the conversion of glucose to gluconic acid and H2O2. H2O2 can oxidize 3,3',5,5'-tetramethylbenzidine (TMB) with the generation a bright-blue color, enabling in-field visualization and surface enhanced Raman scattering (SERS) detection of glucose. Upon the addition of caffeine, 2-aminoterephthalic acid modified MIL-53 can react with the caffeine to form intermolecular hydrogen-bonded complexes, leading to strong cyan fluorescence and significant Raman enhancements. The DNS with multi-channel signal outputs can simultaneously determine glucose and caffeine at concentrations of as low as 3 × 10-8 M and 1.2 × 10-11 M, respectively. Importantly, the DNS-based analytical system not only enables visual discrimination and accurate assay of glucose and caffeine in biofluids, but also exhibits negligible cross-interference between glucose and caffeine determination. The combined characteristics of high selectivity, enhanced accuracy and superior quantitative performance make our platform suitable for the point-of-care monitoring of chronic-disease-related metabolic biomarkers.