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Microwave-assisted Functionalization of Polyethylene glycol and On-resin Peptides for Use in Chain Polymerizations and Hydrogel Formation
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Peptide-responsive photonic hydrogels integrated with deep learning assistance for early MMP-9 detection

Yan Wang1, Mingyi Liu1, Xufang Liu1

  • 1State Key Laboratory of Oral & Maxillofacial Reconstruction and Regeneration & National Clinical Research Center for Oral Diseases & Shaanxi Key Laboratory of Stomatology, Department of Prosthodontics, School of Stomatology, The Fourth Military Medical University, Xi'an, Shaanxi, 710032, China.

Biosensors & Bioelectronics
|January 31, 2026
PubMed

Insights

A novel photonic crystal hydrogel enables rapid, point-of-care detection of matrix metalloproteinase-9 (MMP-9). This MMP-9 sensor offers a cost-effective and accurate alternative to traditional assays for disease diagnostics.

Area of Science:

  • Biomaterials Science
  • Biomedical Engineering
  • Analytical Chemistry

Background:

  • Matrix metalloproteinase-9 (MMP-9) is vital for extracellular matrix remodeling, but its dysregulation links to inflammatory diseases and cancer.
  • Conventional MMP-9 detection methods like ELISA are complex, costly, and time-consuming, hindering point-of-care applications.

Purpose of the Study:

  • To develop a rapid, portable, and cost-effective MMP-9 detection platform.
  • To overcome the limitations of existing MMP-9 diagnostic assays for clinical use.

Main Methods:

  • Synthesized an MMP-9 responsive photonic crystal (PC/PEG-M9SP) hydrogel using 4-arm polyethylene glycol-acrylate and an MMP-9 sensitive peptide.
  • Utilized a Michael-type addition reaction for hydrogel synthesis.
  • Integrated the hydrogel with a deep learning-based smartphone app for detection.

Main Results:

  • The PC/PEG-M9SP hydrogel exhibited a distinct color shift upon MMP-9 cleavage, enabling visual and quantitative detection within 10 minutes.
  • Achieved high sensitivity (10.60 nm mL/ng) and a low detection limit (0.62 ng/mL).
  • Demonstrated strong concordance with ELISA in complex biological fluids, confirming analytical reliability.

Conclusions:

  • The developed hydrogel system offers a rapid, portable, and cost-effective solution for accurate MMP-9 detection.
  • This platform holds significant potential for point-of-care testing and clinical diagnostics.
Keywords:
Deep learningEnzymatic cleavageMMP-9PeptidePhotonic hydrogelPoint-of-care testing

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