Single-walled carbon nanotube biosensor for real-time monitoring of nitric oxide in inflammatory responses
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Author
Zubkovs, Vitalijs
Belcastro, Laura
Sajjadi, Sayyed Hashem
Rabbani, Yahya
Ristaniemi, Aapo
Mdingi, Vuyisa
Peez, Christian
Tognato, Riccardo
Serra, Tiziano
Cattaneo, Stefano
DOI
https://doi.org/10.1016/j.bios.2025.118092
Abstract
Osteoarthritis (OA) is a degenerative inflammatory joint disease affecting millions of people worldwide. The early detection of OA and the continuous monitoring of its progression are essential for managing the disease. In this study, we develop an optical system for monitoring OA-related inflammation by detecting nitric oxide (NO), a molecule that is overproduced in joints during OA. The NO sensor is based on fluorescent single-walled carbon nanotubes (SWCNTs) coated with single-stranded DNA (ssDNA). The sensor fluorescence was characterized in the presence of cells and biological tissue using a custom-built optical shortwave infrared (SWIR) reader with LED excitation centered at 657 nm and 726 nm and emissions collected above 1000 nm. The ssDNA-SWCNTs were embedded in gelatin methacryloyl (GelMA) hydrogels to monitor the release of NO in inflamed (1 ng/mL IL1β) bovine chondrocytes over 48 h. The sensors show a concentration-dependent mechanical stability, maintaining a stable Young's modulus for at least 30 days at 1:10 ssDNA-SWCNT:GelMA mixing ratios (17.8 mg/L SWCNTs). The sensor was incorporated into a custom microfabricated sensor tag that was surgically inserted ex vivo into bovine and human knees. The reader measurements confirm measurable SWIR signal depths of up to 6 mm under the skin and 6 mm under muscle tissue. The measurements further confirm no significant sensor tag displacement after 2500 flexion knee cycles. The custom ssDNA-SWCNT sensor tag and reader thus demonstrate a potential pathway for integrating SWIR technologies into clinical and orthopedic applications.
Publication Reference
Biosensors and Bioelectronics, Vol 293, Issue 118092
Year
2025-10-10
Sponsors
This work was funded through the Swiss Innovation Agency (Innosuisse) under grant 56034.1 IP-LS (NIOXIS).