Ultra-sensitive diagnostic platform utilizing gold nanoparticle integrated in a freestanding hydrogel matrix
Abstract
• 3D porous hydrogel with embedded AuNPs boosts fluorescence signals for ultra-sensitive protein detection. • One-step slit channel lithography integrates AuNPs without complex processing. • Freestanding microparticles improve diffusion and analyte binding efficiency. Fluorescence-based analysis for protein detection has been widely adopted; however, they fall short in achieving ultra-sensitive detection because of their inherently low signal-to-noise ratio at sub-picomolar concentrations. To overcome this limitation, signal amplifying materials such as gold nanoparticles (AuNPs) have been integrated into various detection platforms to enhance fluorescence signals. However, fabrication of such AuNP integrated platforms remains complex, often requiring sophisticated fabrication steps, yet none approach the ultra-sensitive detection range of 10 0 fg mL −1 . In this study, we enabled analysis of captured protein/antibody at 10 0 fg mL −1 concentrations through fluorescence signals utilizing freestanding gold nanoparticle integrated freestanding hydrogel platforms. The platform is fabricated by integrating AuNPs into the hydrogel matrix using a single-step photolithographic technique. The integrated AuNPs significantly enhanced the fluorescence signals compared to controls. Notably, at fg mL −1 levels of fluorophore, the AuNP integrated hydrogels produced a robust optical signal in contrast to negligible responses observed in controls. The platform’s versatility was validated using tumor necrosis factor-alpha antibody (TNF-α Ab), achieving detection at 10 0 fg mL −1 . By synergizing the hydrogels’ porous structure with AuNPs’ signal amplification, this platform successfully achieves fluorescence-based ultra-sensitive protein/antibody detection.
Fields of Study & Subjects
Advanced Biosensing Techniques and Applications
Gold and Silver Nanoparticles Synthesis and Applications
Biosensors and Analytical Detection
Publication details
- Journal / source
- Methods
- Publisher
- Elsevier BV
- Volume
- 248
- Pages
- 43–52
- Publication date
- 3 February 2026
- Language
- EN