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Electrochemiluminescence behaviour of m-CNNS quenched by CeO2@PDA composites for sensitive detection of BNP

电化学发光 化学 检出限 共价键 接受者 色谱法 有机化学 凝聚态物理 物理
作者
Asghar Ali,Bin Xing,Malik Saddam Khan,Ning Ma,Romana Manzoor,Dan Wu,Qin Wei
出处
期刊:Journal of Electroanalytical Chemistry [Elsevier]
卷期号:862: 113970-113970 被引量:19
标识
DOI:10.1016/j.jelechem.2020.113970
摘要

Heart failure is one of the common disabling states and serious illness among medical disorders that may lead to death. Brain natriuretic peptide (BNP) has been recognized as a new biomarker of outstanding prognosis-predictive capability for heart failure. In this work, modified carbon nitride nanosheets (m-CNNS) were used as the part of this sensing platform could generate stronger ECL emission and the CeO2@Polydopamine (CeO2@PDA) composites firstly worked as effective ECL signal quencher. Moreover, there was a suitable overlap between the absorption spectra of CeO2@PDA and ECL spectra of m-CNNS, causing the remarkable decline in ECL signal. In particular, a novel ECL-RET (electrochemiluminescence resonance energy transfer) system between m-CNNS as ECL donor while CeO2@PDA as ECL acceptor was established. CeO2@PDA composites were tightly linked to the secondary antibody (Ab2) via covalent bonding owing to the reactive quinones on the surface of the PDA film. The primary antibody (Ab1) and m-CNNS are connected via carboxylic groups of 1-pyrene butyric acid (Py-COOH, sodium salt) easily employing EDC/NHS activation, a common crosslinking approach. By employing K2S2O8 as a coreactant, ECL behaviour of m-CNNS was observed. Under optimal conditions, BNP concentration was detected in the range of 0.5 pg/mL–100 ng/mL with the detection limit of 0.01 pg/mL (S/N = 3). Featuring high sensitivity, wider linear range, excellent repeatability and selectivity, this ECL-RET immunosensor opened a novel path to realize a reliable sensitive detection of BNP, which may also be applied to determine other biomarkers. It was noteworthy that the proposed method was applied to real serum samples accompanied by good recovery range of 102.8–103.2%, indicating that the recommended method was of good accuracy for BNP detection.
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