Abstract

Urinary stones (US) are common urological disease with a high incidence and a risk of comorbidities. An accurate and high-throughput strategy is greatly needed for US diagnosis. Herein, we designed metal-polyphenol networks mediated Au-Pt hybrid nanoparticles (AuMPN-Pt HNPs) and fabricated a dual-functional nanoplatform inte grating LDI-MS analysis and colorimetric assay for US diagnosis and subtype classification. The AuMPN-Pt HNPs exhibited superior LDI-MS performance with high sensitivity (limit of detection (LOD) < 2 µM) and good MS signal reproducibility (coefficients of variation (CVs) < 10 %) for accurate detection of metabolites. Meanwhile, AuMPN-Pt HNPs presented excellent peroxidase (POD)-like activity, allowing for direct and rapid detection of uric acid (UA) assisted by uricase with a LOD of 9.43 µM. Using the AuMPN-Pt HNPs assisted LDI-MS platform, we successfully achieved non-invasive US diagnosis by metabolic profiling of urine samples from US patients and the healthy controls (HCs), as well as subtype discrimination of calcium oxalate stones (CaOx stones) from UA stones by combining analysis of metabolic fingerprints from serum and urine samples. The subtype discrimi nation results were further verified by colorimetric platform for serum UA level analysis. The dual-functional nanoplatform exhibited outstanding sensitivity and specificity, providing innovative insights into disease diagnosis and subtype differentiation.

Scheme. 1. Overall schematics of dual-functional nanoplatform based on MPN-mediated Au-Pt hybrid nanoparticles (AuMPN-Pt HNPs) integrating LDI-MS and colorimetry analysis.

Fig. 1. AuMPN-Pt HNPs based dual-functional platform for urinary stones (US) diagnosis and classification. (a) Scheme illustration of LDI-MS platform for recording metabolic fingerprints (MFs) from urine and serum samples and colorimetric assay for the detection of serum UA based on AuMPN-Pt HNPs. (b) Typical mass spectra of urine samples from US and HC individuals at m/z of 80-400. (c) Heatmap of 354 m/z features extract from 129 UMFs, including 79 UA patients (69 CaOx stones and 10 UA stones) and 50 HCs. (d) OPLS-DA for the discrimination of UMFs from 79 US patients (red) and 50 HCs (blue). (e) The ROC curve of train cohort and test cohort based on NN algorithm. (f) The ROC curve of for subtype classification based on NN algorithm. (g) AuMPN-Pt HNPs based colorimetric assay and commercial kit for the detection of serum UA level from 4 CaOx stones and 5 UA stones. (h) Linear correlation between the UA level obtained from the AuMPN-Pt HNPs based colorimetric assay and commercial kit, with R2 of 0.9087.

https://doi.org/10.1016/j.nantod.2025.102965