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A Plasmonic Mass Spectrometry Approach for Detection of Small Nutrients and Toxins 被引量:1
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作者 Shu Wu Linxi Qian +6 位作者 Lin Huang xuming sun Haiyang Su Deepanjali D.Gurav Mawei Jiang Wei Cai Kun Qian 《Nano-Micro Letters》 SCIE EI CAS 2018年第3期155-163,共9页
Nutriology relies on advanced analytical tools to study the molecular compositions of food and provide key information on sample quality/safety. Small nutrients detection is challenging due to the high diversity and b... Nutriology relies on advanced analytical tools to study the molecular compositions of food and provide key information on sample quality/safety. Small nutrients detection is challenging due to the high diversity and broad dynamic range of molecules in food samples, and a further issue is to track low abundance toxins. Herein, we developed a novel plasmonic matrix-assisted laser desorption/ionization mass spectrometry(MALDI MS)approach to detect small nutrients and toxins in complex biological emulsion samples. Silver nanoshells(SiO_2@-Ag) with optimized structures were used as matrices andachieved direct analysis of ~ 6 n L of human breast milk without any enrichment or separation. We performed identification and quantitation of small nutrients and toxins with limit-of-detection down to 0.4 pmol(for melamine) and reaction time shortened to minutes, which is superior to the conventional biochemical method currently in use. The developed approach contributes to the near-future application of MALDI MS in a broad field and personalized design of plasmonic materials for real-case bio-analysis. 展开更多
关键词 Plasmonic materials Laser desorption/ionization Mass spectrometry Small nutrients TOXINS
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Extraction, detection, and profiling of serum biomarkers using designed Fe3O4@SiO2@HA core-shell particles 被引量:2
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作者 Chandrababu Rejeeth Xuechao Pang +8 位作者 Ru Zhang Wei Xu xuming sun Bin Liu Jiatao Lou Jingjing Wan Hongchen Gu Wei Yan Kun Qian 《Nano Research》 SCIE EI CAS CSCD 2018年第1期68-79,共12页
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 ... 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 Fe304@SiOa@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 I ng/mL to 10 ~tg/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. 展开更多
关键词 ligand-protein interaction magnetic particles serum biomarkers cluster of differentiation44(CD44) sensors mass spectrometry
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