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A target-driven DNA-based molecular machine for rapid and homogeneous detection of arginine-vasopressin.
Tan, Haocheng; Chen, Lu; Li, Xinyi; Li, Mengyuan; Zhao, Meiping.
Afiliação
  • Tan H; Beijing National Laboratory for Molecular Sciences, MOE Key Laboratory of Bioorganic Chemistry and Molecular Engineering, College of Chemistry and Molecular Engineering, Peking University, Beijing 100871, China. mengyuanli@pku.edu.cn mpzhao@pku.edu.cn.
Analyst ; 145(3): 880-886, 2020 Feb 03.
Article em En | MEDLINE | ID: mdl-31825412
Rapid detection of physiological changes of neuropeptides is of great importance as they are involved in a wide range of physiological processes and behaviors. Abnormalities in their expression level are correlated with various neurological diseases. However, current methods such as radioimmunoassay, enzyme-linked immunosorbent assays and liquid chromatography tandem mass spectrometry relied on cumbersome operation steps and could not rapidly provide the information of their concentration fluctuations. Thus motivated, we developed a target-driven DNA-based molecular machine that could be triggered only in the presence of a specific target neuropeptide. Using arginine-vasopressin (AVP) as a model neuropeptide, we integrated the DNA-based molecular machine with fluorescence signal transduction and amplification technology. The assay was rapid and homogeneous, which offered a linear range of 75-700 pM and a limit-of-detection as low as 75 pM. It holds great potential for further applications in real-time monitoring of the variations of the AVP level in biological samples.
Assuntos

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: DNA / Arginina Vasopressina Tipo de estudo: Diagnostic_studies / Prognostic_studies Limite: Humans Idioma: En Revista: Analyst Ano de publicação: 2020 Tipo de documento: Article

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: DNA / Arginina Vasopressina Tipo de estudo: Diagnostic_studies / Prognostic_studies Limite: Humans Idioma: En Revista: Analyst Ano de publicação: 2020 Tipo de documento: Article