Polydopamine Modified Carbon Nitride and PAMAM Assembled Electrochemical Immunosensor for Detection of Indole-3-Acetic Acid
文献类型: 外文期刊
第一作者: Zhang, Jian
作者: Zhang, Jian;Mijakovic, Ivan;Pandit, Santosh;Li, Aixue;Yu, Xin;Mijakovic, Ivan
作者机构:
关键词: carbon nitride; polyamidoamine; polydopamine; indole-3-acetic acid; immunosensor
期刊名称:CHEMELECTROCHEM ( 影响因子:3.5; 五年影响因子:3.9 )
ISSN: 2196-0216
年卷期: 2024 年 11 卷 11 期
页码:
收录情况: SCI
摘要: Indole-3-acetic acid (IAA) assumes a pivotal role as a phytohormone of utmost importance, intricately orchestrating the nuanced processes associated with the growth and developmental trajectories of botanical organisms. In this study, we have designed and fabricated a label-free electrochemical impedance immunosensor for the precise detection of IAA. The detection strategy predominantly relied upon polydopamine modified carbon nitride (C3N4) nanosheets (PCN) and polyamidoamine (PAMAM) dendrimer. Through the modification with PCN and PAMAM, the electrode has increased the active area and enhanced the immobilization capacity of antibodies for IAA. The immunosensor's ability to capture IAA was significantly improved by enhancing the immunoreaction between the antibody and antigen. This enhancement led to an increased response in the electrochemical behavior of the Fe(CN)63-/4- redox probe. The impedance immunosensor developed exhibits remarkable sensitivity, exceptional selectivity, and consistent performance in the detection of IAA. This assay method, with the potential to replace antibodies, could offer an alternative approach for detecting various phytohormones. An electrochemical immunosensor was developed for precise detection of indole-3-acetic acid (IAA), a crucial plant phytohormone. Utilizing polydopamine modified C3N4 nanosheets (PCN) and polyamidoamine dendrimer (PAMAM), the sensor enhanced antibody immobilization, improving IAA capture and electrochemical response. The method offers high sensitivity, selectivity, and potential for broader phytohormone detection, presenting an alternative to IAA-based detection. image
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