An Efficient Detection Platform Based on Mesoporous Au@Cr2O3 Particles with Schwarz P Surface for Precise Periodontitis Metabolite Profiling

Matrix materials with high desorption and ionization efficiency are crucial for the sensitive and accurate metabolite profiling in matrix‐assisted laser desorption ionization mass spectrometry (MALDI‐MS). Herein, we develop an efficient detection platform based on Au nanoparticles decorated mesoporous Cr 2 O 3 (Au@mCr 2 O 3 ) particles with a single primitive continuous structure (i.e., Schwarz P surface) as the matrix. Owing to the low‐tortuosity mesoporous pathways and customized chemical composition, the Au@mCr 2 O 3 exhibits high‐efficiency light absorption and electron transfer, showing great potential for sensitive, reproducible, and selective metabolite detection. Therefore, it is considered as a high‐performance and reliable matrix material for metabolic biomarkers screening. As a proof of concept, the Au@mCr 2 O 3 ‐based detection platform decodes the saliva metabolic fingerprints. With the assistance of machine learning, the platform achieves high diagnostic performance for periodontitis, with the areas under the curve of 0.875–0.934. Furthermore, a simplified biomarker panel is established, which provides a deeper mechanism understanding of the metabolic alternation of periodontitis and offers new insights into its diagnosis and pathogenesis. A non‐invasive periodontitis diagnosis platform was developed using Au nanoparticles‐decorated mesoporous Cr 2 O 3 (Au@mCr 2 O 3 ) particles with Schwarz P surface as matrix for saliva metabolic fingerprinting (SMFs) analysis via MALDI‐MS. With the assistance of machine learning of SMFs, this platform enables efficient diagnosis and the screening of potential biomarkers, thus establishing a simplified diagnostic model and elucidating the possible mechanism about periodontitis pathogenesis.