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A scalable and cost-effective plasmonic enhanced fluorescence platform for high-sensitivity detection of thyroid
Chenyu Shi1, Ying Yue1, Yichen Wang2
1State Key Laboratory of Supramolecular Structure and Materials, Center for Supramolecular Chemical Biology, College of Chemistry, Jilin University, Changchun, 130012, PR China; Joint Laboratory of Opto-Functional Theranostics in Medicine and Chemistry, The First Hospital of Jilin University, Changchun, 130021, PR China.
None:
Fluorescence-based protein microarrays present rapid, high-throughput disease biomarker detection but suffer from limited sensitivity and high background. Plasmonic enhanced fluorescence (PEF) using metallic nanogaps addresses these issues via localized surface plasmon resonance (LSPR), yet conventional fabrication methods are costly and complex. Here, we report a thermal annealed plasmonic nanogap (TAP-Nano) platform fabricated by electrostatic self-assembly of poly(diallyldimethylammonium chloride) (PDDA) and gold nanoparticles (AuNPs) on glass slides, followed by thermal annealing to generate dense and uniform plasmonic nanogaps. TAP-Nano is cost-effective (<$0.5 per chip), scalable (127 × 85 mm2), and enhances fluorescence signals by two orders of magnitude compared to conventional substrates, achieving the limit of detection (LOD) in pg mL-1. Validated for thyroid function biomarkers in clinical serum samples, TAP-Nano demonstrated specificities of 98.20 %, 100 %, and 96.67 % and sensitivities of 97.44 %, 99.17 %, and 90.52 % for thyroid stimulating hormone (TSH), thyroid peroxidase antibody (TPOAb), and thyroglobulin antibody (TgAb) in 206 samples, respectively. Simultaneous TSH/free triiodothyronine (FT3) detection in 15 samples achieved 100 % specificity and sensitivity. The assay requires only 0.6 μL of serum, completes in less than 80 min, and spans a 5-log dynamic range. Combining simplicity, scalability, and ultrahigh sensitivity, TAP-Nano holds significant potential for multiplexed clinical diagnostics, advancing next-generation PEF-based biosensing platforms.
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