化学
色谱法
萃取(化学)
整体
样品制备
环境分析
固相萃取
分析物
试剂
有机化学
催化作用
作者
Andrea Cerrato,Sara Elsa Aita,Chiara Cavaliere,Aldo Laganà,Carmela Maria Montone,Susy Piovesana,Enrico Taglioni,Anna Laura Capriotti
标识
DOI:10.1021/acs.analchem.3c05706
摘要
Multicomponent reactions offer efficient and environmentally friendly strategies for preparing monoliths suitable for applications in analytical chemistry. In the described study, a multicomponent reaction was utilized for the one-pot miniaturized preparation of a poly(propargyl amine) polymer inside commercial silica-lined PEEK tubing. The reaction involved only small amounts of reagents and was characterized by atom economy. The resulting monolithic column was incorporated into an autosampler system for the online extraction and cleanup of β-estradiol from human serum. Sample pretreatment was simplified to a simple dilution with methanol and centrifugation to remove proteins. The resulting platform included LC–MS analysis in multiple reaction monitoring for quantitative analysis of β-estradiol. The method was validated in serum, demonstrating practical applicability for the monitoring of fertile women. Recoveries were above 94%, and LOD and LOQ values at 0.008 and 0.18 ng mL–1, respectively. The developed platform proved to be competitive with previous methods for solid-phase microextraction of β-estradiol in serum, with comparable recovery and sensitivity but with the advantage of nearly complete automation. The environmental impact of the process was evaluated as acceptable due to the miniaturization of the monolith synthesis and the automation of extraction. The drawback associated with the LC–MS technique can be reduced by the inclusion of additional analytes in a single investigation. The work demonstrates that multicomponent reactions are versatile, economical, and possibly a green methodology for producing reversed-phase and mixed-mode sorbents, enabling miniaturization of the entire analytical procedure from the preparation of extraction sorbents to analysis.
科研通智能强力驱动
Strongly Powered by AbleSci AI