Hollow multishelled heterostructures with enhanced performance for laser desorption/ionization mass spectrometry based metabolic diagnosis

被引:3
|
作者
Pei, Congcong [1 ]
Su, Rui [2 ,3 ]
Lu, Songting [1 ]
Chen, Xiaonan [1 ]
Ding, Yajie [1 ]
Li, Rongxin [1 ]
Shu, Weikang [1 ]
Zeng, Yu [1 ]
Lin, Yingying [1 ]
Xu, Liang [2 ]
Mi, Yuqiang [2 ,3 ]
Wan, Jingjing [1 ]
机构
[1] East China Normal Univ, Sch Chem & Mol Engn, Shanghai 200241, Peoples R China
[2] Tianjin Med Univ, Tianjin Peoples Hosp 2, Tianjin 300192, Peoples R China
[3] Tianjin Inst Hepatol, Tianjin 300192, Peoples R China
基金
中国国家自然科学基金;
关键词
HEPATOCELLULAR-CARCINOMA; IDENTIFICATION; FINGERPRINTS; DISCOVERY; MATRIX;
D O I
10.1039/d3tb00766a
中图分类号
TB3 [工程材料学]; R318.08 [生物材料学];
学科分类号
0805 ; 080501 ; 080502 ;
摘要
High-performance metabolic diagnosis-based laser desorption/ionization mass spectrometry (LDI-MS) improves the precision diagnosis of diseases and subsequent treatment. Inorganic matrices are promising for the detection of metabolites by LDI-MS, while the structure and component impacts of the matrices on the LDI process are still under investigation. Here, we designed a multiple-shelled ZnMn2O4/(Co, Mn)(Co, Mn)(2)O-4 (ZMO/CMO) as the matrix from calcined MOF-on-MOF for detecting metabolites in LDI-MS and clarified the synergistic impacts of multiple-shells and the heterostructure on LDI efficiency. The ZMO/CMO heterostructure allowed 3-5 fold signal enhancement compared with ZMO and CMO with the same morphology. Furthermore, the ZMO/CMO heterostructure with a triple-shelled hollow structure displayed a 3-fold signal enhancement compared to its nanoparticle counterpart. Taken together, the triple-shelled hollow ZMO/CMO exhibits 102-fold signal enhancement compared to the commercial matrix products (e.g., DHB and DHAP), allowing for sensitive metabolic profiling in bio-detection. We directly extracted metabolic patterns by the optimized triple-shelled hollow ZMO/CMO particle-assisted LDI-MS within 1 s using 100 nL of serum and used machine learning as the readout to distinguish hepatocellular carcinoma from healthy controls with the area under the curve value of 0.984. Our approach guides us in matrix design for LDI-MS metabolic analysis and drives the development of a nanomaterial-based LDI-MS platform toward precision diagnosis.
引用
收藏
页码:8206 / 8215
页数:10
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