High-performance bottom gate carbon nanotube field-effect transistor immunosensor for detecting glial fibrillary acidic protein: A biomarker for traumatic brain injury
- Int J Biol Macromol. 2025 Jun;311(Pt 2):143884. doi: 10.1016/j.ijbiomac.2025.143884.
- 1. School of Chemical Engineering, Yeungnam University, Gyeongsan, Gyeongbuk 38541, Republic of Korea. Electronic address: [email protected].
- 2. Department of Chemical Engineering Technology, College of Applied Industrial Technology, Jazan University, Jazan 45142, Saudi Arabia.
- 3. Department of Mechanical Engineering, College of Engineering, Jazan University, P. O. Box 114, Jazan 45142, Saudi Arabia. Electronic address: [email protected].
- 4. Department of Biochemistry, Faculty of Science, King Abdulaziz University, Jeddah 21452, Saudi Arabia.
- 5. Department of Mechanical Engineering, College of Engineering, Jazan University, P. O. Box 114, Jazan 45142, Saudi Arabia.
Glial fibrillary acidic protein (GFAP) is a biomarker expressed in the central nervous system and its serum levels increase following Traumatic Brain Injury (TBI). Serum-based GFAP has the potential to serve as a diagnostic tool for the early detection and management of TBI, thereby helping to prevent death and long-term disability. The primary objective of this study was to develop an immunosensor capable of timely GFAP detection, aiming to reduce radiation exposure and healthcare costs. In this study, a bottom gate carbon nanotube field-effect transistor (CNT-FET) immunosensor was fabricated for GFAP detection. Anti-GFAP was immobilized on the CNTs and the sensor was blocked with bovine serum albumin to prevent nonspecific protein binding. Real-time measurements demonstrated the ability of the sensor to detect increasing concentrations of GFAP in buffer solution. The immunosensor exhibited a linear detection range of 0.1-1000 pg/mL, with a limit of detection (LOD) of 0.1 pg/mL in phosphate-buffered saline (PBS). GFAP levels in commercial human serum were determined using standard addition and recovery methods and results were validated against the conventional ELISA method, showing high accuracy and precision. The immunosensor demonstrates high sensitivity and selectivity capabilities, with strong potential for real-world applications in clinical diagnostics.
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