代谢物分析
仿形(计算机编程)
材料科学
代谢物
纳米技术
计算生物学
计算机科学
生物
生物化学
操作系统
作者
Zhiyu Li,Weili Peng,Juan Zhou,Shaoxuan Shui,Y Liu,Tan Li,Xiaohui Zhan,Yuanyuan Chen,Fang Lan,Binwu Ying,Yao Wu
标识
DOI:10.1002/adma.202312799
摘要
Abstract It is challenging to detect and differentiate multiple diseases with high complexity/similarity from the same organ. Metabolic analysis based on nanomatrix‐assisted laser desorption/ionization mass spectrometry (NMALDI‐MS) is a promising platform for disease diagnosis, while the enhanced property of its core nanomatrix materials has plenty of room for improvement. Herein, a multidimensional interactive cascade nanochip composed of iron oxide nanoparticles (FeNPs)/MXene/gold nanoparticles (AuNPs), IMG, is reported for serum metabolic profiling to achieve high‐throughput detection of multiple liver diseases. MXene serves as a multi‐binding site and an electron‐hole source for ionization during NMALDI‐MS analysis. Introduction of AuNPs with surface plasmon resonance (SPR) properties facilitates surface charge accumulation and rapid energy conversion. FeNPs are integrated into the MXene/Au nanocomposite to sharply reduce the thermal conductivity of the nanochip with negligible heat loss for strong thermally‐driven desorption, and construct a multi‐interaction proton transport pathway with MXene and AuNPs for strong ionization. Analysis of these enhanced serum fingerprint signals detected from the IMG nanochip through a neural network model results in differentiation of multiple liver diseases via a single pass and revelation of potential metabolic biomarkers. The promising method can rapidly and accurately screen various liver diseases, thus allowing timely treatment of liver diseases.
科研通智能强力驱动
Strongly Powered by AbleSci AI