Lighting up the gold/silver nanoclusters via confinement effect for the quantification and discrimination of sulfur-containing compounds.

Sulfur-containing compounds (SCCs) play critical roles in physiological and pathological processes, but their abnormal levels are linked to diseases such as cancer and neurodegenerative diseases. Consequently, the development of accurate quantification and discrimination methods for SCCs is of great significance, providing a powerful tool for the early diagnosis of diseases. In the present study, we designed a confinement-enhanced fluorescence strategy utilizing zirconium-layered double hydroxide microspheres (ZrLDHMs) to encapsulate bimetallic AuAg nanoclusters (AuAgNCs), achieving remarkable enhancement in fluorescence properties including emission intensity, quantum yield, and fluorescence lifetime. Capitalizing on the redox activity of 2,6-dichlorophenol indophenol (DCIP) and the reducing ability of SCCs, a novel dual-mode (fluorescence/colorimetry) sensing platform was constructed based on ZrLDHMs@AuAgNCs for rapid SCCs detection. The fabricated sensor exhibited high sensitivity toward five SCCs (GSH, Cys, MPA, NaS, and NaSO). Taking GSH as a representative, the sensor demonstrated limit of detection of 0.64 μM (fluorescence) and 0.09 μM (colorimetry) with a linear range of 2-70 μM at pH 7.0. Furthermore, by leveraging the differences in the reduction capabilities of DCIP among various types of SCCs, different responses are generated on the sensor array, thereby forming "fingerprint" features. Based on the extracted fingerprint features, the sensor array enabled rapid discrimination of multiple SCCs with high specificity. It was successfully applied to discriminate different types of SCCs in real serum and urine samples. Notably, this work not only demonstrates ZrLDHMs as effective confinement matrices for metal nanoclusters fluorescence enhancement, but also establishes a versatile sensing platform for the quantification and discrimination of SCCs, offering a versatile tool for clinical diagnostics.