Immuno-RAFT Fluorescence Array Sensing for High-Throughput Analysis of CD81 Protein

This study introduces a highly sensitive fluorescence array that leverages immunosorbent reversible addition-fragmentation chain transfer (immuno-RAFT) signal amplification for detecting CD81 protein, a key biomarker used to diagnose preeclampsia. By integrating the operational efficiency of traditional enzyme-linked immunosorbent assay (ELISA) in 96-well plates with the robust signal amplification capabilities of RAFT technology, this method enables rapid and quantitative detection of low-concentration CD81 protein. This advancement provides substantial theoretical and technical support for the analysis of complex clinical samples. The inclusion of molybdenum disulfide (MoS₂) catalyst and piperine in the RAFT solution significantly enhances fluorescence signals. The optimized detection system not only demonstrates a strong correlation between fluorescence intensity and protein concentration but also exhibits exceptional anti-interference capabilities under serum and artificial urine conditions, validating its practicality for real-world sample analysis. Further characterization through particle size analysis and scanning electron microscopy (SEM) reveals that the fluorescent polymers formed after the RAFT reaction display excellent polymerization and uniform network structures, which underpin the signal amplification mechanism. Additionally, the method shows remarkable long-term stability, with fluorescence signals retaining over 95% of their initial intensity after 7 days of low-temperature storage, highlighting its potential for extended use. This method detects trace small concentrations, surpassing the sensitivity achievable with conventional techniques. In conclusion, the immuno-RAFT fluorescence array sensing method overcomes the limitations of traditional detection techniques. Future applications of this method could extend to the detection of other protein biomarkers, thereby advancing the role of biosensors in clinical diagnostics and disease management.