[ Instrument Network Instrument Development ] Recently, Liu Jian, a researcher at the National Key Laboratory of Catalysis, Dalian Institute of Chemical Physics, Chinese Academy of Sciences, and Qian Kun, a researcher at the School of Biomedical Engineering, Shanghai Jiaotong University, have innovatively applied multifunctional platinum-based nanometers. The reactor can simultaneously detect and molecularly classify metabolites in pancreatic cancer detection.
The mortality rate of pancreatic cancer is as high as 98%, and it has the title of â€œKing of Cancerâ€. An effective early diagnosis can increase the five-year survival rate of pancreatic cancer to 67%. However, current blood tests for pancreatic cancer only target specific protein biomarkers such as CA19-9, which have limited diagnostic performance and specificity of only about 30%. Metabolomics is at the very end of the biochemical pathway and is analyzed for ongoing biochemical processes, most closely related to disease phenotype. The high concentration of protein and salt components in complex biological systems restricts the in situ detection of metabolomes. Therefore, it is still necessary to rely on special detection techniques and functional materials for analytical determination of bedside detection (POC) in metabolomics.
In response to the above problems, Liu Jian team and Qian Kun team cooperated to build a multi-functional platform for real-time detection and molecular typing of metabolites based on the basic structure of nanoreactor and multi-functional platinum nanoreactor. The optimized multifunctional platinum-based nanoreactor has two characteristics. First, it has high catalytic activity and can simultaneously replace glucose oxidase (GOx) and horseradish peroxidase (HRP) to achieve specific metabolism such as glucose. The color detection of the marker takes only 5 minutes. The other is the analysis of the blood metabolome by laser desorption ionization mass spectrometry, which achieves accurate, non-invasive liquid biopsy of pancreatic cancer with a diagnostic sensitivity of 84% and a specificity of 92%. This work provides new ideas for the medical diagnostic applications of nanoreactors, providing new insights not only for metabolic changes in patients with pancreatic cancer, but also for the accurate diagnosis of disease.
The above work was funded by the Xingliao Talents Program and was recently published on Matter.
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