研究目的
To develop a luminescent nanosensor that bypasses real-time light excitation for multiplex differentiation of cancer exosomes, aiming to overcome challenges of high specificity and low background in optical detection.
研究成果
The ASPNC-based afterglow sensor minimizes background signals by eliminating real-time light excitation, achieving significantly lower LOD than fluorescence in complex media. It allows multiplex detection of exosomal proteins through aptamer variation, enabling accurate identification of exosome source cells for cancer diagnosis, with potential for high-throughput applications and simplified sample processing.
研究不足
The nanosensor requires careful selection of appropriate aptamers, which is crucial for specificity and sensitivity, and may limit its broad applicability without optimized aptamers.
1：Experimental Design and Method Selection:
The study involves synthesizing a near-infrared afterglow semiconducting polyelectrolyte (ASP) and forming nanocomplexes (ASPNC) with quencher-tagged aptamers for specific detection of exosomes. The sensing mechanism relies on electron transfer quenching and signal turn-on upon exosome binding.
2：Sample Selection and Data Sources:
Exosomes secreted from various cell lines (e.g., Hela, MCF-7, SKOV3, HepG2, chondrocytes) were used.
3：List of Experimental Equipment and Materials:
Equipment includes dynamic light scattering (DLS) for size measurement, transmission electron microscope (TEM) for morphology, IVIS bioluminescence for afterglow imaging, and fluorescence spectrometer. Materials include ASP polymer, BHQ-2 quencher, aptamers (e.g., AptCD63), and exosome samples.
4：Experimental Procedures and Operational Workflow:
Synthesis of ASP via Pd-catalyzed Stille coupling, formation of ASPN nanoparticles, complexation with aptamers to form ASPNC, optical property measurements (absorption, fluorescence, afterglow), and detection of exosomes in different media (PBS, mouse plasma, cell culture medium).
5：Data Analysis Methods:
Signal recovery ratios were calculated, limit of detection (LOD) determined, and statistical analysis performed with standard deviations and significance tests.
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