Metabolomics has attracted increasing interest in recent years because metabolites offer a unique and dynamic layer of biological insight beyond genomics and proteomics. Owing to their rapid turnover, analytical techniques that enable fast, highly sensitive detection with minimal sample input are in strong demand. Matrix-assisted laser desorption/ionization mass spectrometry (MALDI MS) is a powerful molecular analysis tool with high sensitivity and specificity, requiring only 0.5-1 µL of sample. However, the use of organic matrices generates significant background interference in the low mass range, which limits its application in metabolite detection. To address this challenge, this study introduces the first-of-its-kind nano-bomb nanostructure-initiator mass spectrometry (NB-NIMS) for sensitive metabolite detection. Instead of organic matrices, NB-NIMS utilizes initiator-loaded rationally designed mesoporous carbon hollow spheres (MCHS) to enhance analyte desorption efficiency. MCHS feature large hollow cavities (~230 nm diameter) and radial trumpet-like pore structures (~11 nm), enabling efficient initiator loading. Upon laser irradiation, the initiator-loaded MCHS act as nano-bombs, triggering rapid and concentrated vaporization that markedly enhances analyte desorption and achieves attomolar-level detection sensitivity. Using this platform, metabolic fingerprints were constructed to differentiate macrophage phenotypes. This work represents a significant advancement in mass spectrometry for ultra-sensitive small-molecule detection in complex biofluids.

Serum biomarkers in the form of proteins (e.g. cluster of differentiation-44 (CD44)) have been demonstrated to have high clinical sensitivity and specificity for disease diagnosis and prognosis. Owing to the high sample complexity and low molecular abundance in serum, the detection and profiling of biomarkers rely on efficient extraction by materials and devices, mostly using immunoassays via antibody-antigen recognition. Antibody-free approaches are promising and need to be developed for real-case applications in serum to address the limitations of antibody-based techniques in terms of robustness, expense, and throughput. In this work, we demonstrated a novel approach using hyaluronic acid (HA)-modified materials/devices for the extraction, detection, and profiling of serum biomarkers via ligand-protein interactions. We constructed Fe₃O₄@SiO₂@HA particles with different sizes through layer-by-layer assembly and for the first time applied HA-functionalized particles in the facile extraction and sequence identification of CD44 in serum by mass spectrometry. We also first validated HA-CD44 binding through electrochemical sensing using HA-modified electrodes in both standard solutions and diluted serum samples, achieving a detection limit of ~0.6 ng/mL and a linear response range from 1 ng/mL to 10 μg/mL. Furthermore, we performed profiling of HA-binding serum proteome, providing a new preliminary benchmark for the construction of future databases, and we investigated selected surface chemistries of particles for the capture of proteins in serum. Our work not only resulted in the development of a platform technology for CD44 extraction/detection and HA-binding proteome identification, but also guided the design of ligand affinity-based approaches for antibody-free analysis of serum biomarkers towards diagnostic applications.