Single-Molecule Sensing of Acidic Catecholamine Metabolites Using a Programmable Nanopore.

Hu, Chengzhen; Jia, Wendong; Liu, Yao; Wang, Yuqin; Zhang, Panke; Chen, Hong-Yuan; Huang, Shuo

Hu, Chengzhen; Jia, Wendong; Liu, Yao; Wang, Yuqin; Zhang, Panke; Chen, Hong-Yuan; Huang, Shuo.

Afiliação

Hu C; State Key Laboratory of Analytical Chemistry for Life Sciences, School of Chemistry and Chemical Engineering, Nanjing University, 210023, Nanjing, China.
Jia W; Chemistry and Biomedicine Innovation Center (ChemBIC), Nanjing University, 210023, Nanjing, China.
Liu Y; State Key Laboratory of Analytical Chemistry for Life Sciences, School of Chemistry and Chemical Engineering, Nanjing University, 210023, Nanjing, China.
Wang Y; Chemistry and Biomedicine Innovation Center (ChemBIC), Nanjing University, 210023, Nanjing, China.
Zhang P; State Key Laboratory of Analytical Chemistry for Life Sciences, School of Chemistry and Chemical Engineering, Nanjing University, 210023, Nanjing, China.
Chen HY; Chemistry and Biomedicine Innovation Center (ChemBIC), Nanjing University, 210023, Nanjing, China.
Huang S; State Key Laboratory of Analytical Chemistry for Life Sciences, School of Chemistry and Chemical Engineering, Nanjing University, 210023, Nanjing, China.

Chemistry ; 28(44): e202201033, 2022 Aug 04.

Article em En | MEDLINE | ID: mdl-35593037

Assuntos

Hidrocarbonetos Aromáticos; Nanoporos; Ácido 3,4-Di-Hidroxifenilacético; Aminas; Catecolaminas

Palavras-chave

acidic catecholamine metabolites; machine learning; nanopore; phenylboronic acid; single-molecule

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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Nanoporos / Hidrocarbonetos Aromáticos Idioma: En Revista: Chemistry Assunto da revista: QUIMICA Ano de publicação: 2022 Tipo de documento: Article País de afiliação: China

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