荧光
光漂白
生物传感器
电化学发光
化学
免疫分析
纳米技术
检出限
胶体金
材料科学
纳米颗粒
色谱法
物理
抗体
生物
量子力学
免疫学
作者
Weijie Wu,Mengfei Shen,Xinyi Liu,Lisong Shen,Ke Xing,Wanwan Li
标识
DOI:10.1016/j.bios.2019.111912
摘要
Aggregation-induced emission luminogens (AIEgens) have attracted considerable interest for application towards the development of various biosensors due to their unique optical properties. However, the major challenge associated with generating a suitable fluorescent signal for constructing an AIEgens-based immunoassay platform, is the complex surface modification and additional chemical reaction required to activate the AIE process. This work reports a novel AIEgens nanobeads-based fluorescence-linked immunosorbent assay (FLISA) platform wherein the fluorescent labels are hexaphenylsilole (HPS) nanobeads, which were synthesized through Shirasu porous glass (SPG) membrane emulsification method and could provide a strong, direct fluorescent signal without any pretreatment. Moreover, the particle-based signal amplification effect affords this platform significantly improved detection sensitivity for carcinoembryonic antigen (CEA) quantitation. Compared to FLISA which uses R-phycoerythrin (PE) or commercial green QDs nanobeads as fluorescent labels, this AIEgens nanobeads-based FLISA platform exhibits detection sensitivity improved up to 45-fold and 12-fold, respectively. Clinical validation experiments applying this AIEgens nanobeads-based FLISA immunoassay platform to analyze human serum samples produce results consistent with those obtained by the clinical gold-standard method, electrochemiluminescence immunoassay (ECLIA). The strong photobleaching resistance and excellent fluorescent stability of the HPS nanobeads negate the need for light shielding, which improves the efficiency and makes the operating conditions more comfortable. Thus, this AIEgens nanobeads-based FLISA platform, with attractive features including direct fluorescent signal generation and significant signal amplification, creates a new, versatile route for the application of AIEgens in biosensors and clinical diagnosis.
科研通智能强力驱动
Strongly Powered by AbleSci AI