Nanomaterial-enhanced biosensors for traumatic brain injury biomarker detection: a review of analytical performance, machine learning integration, clinical validation, and point-of-care translation
Abstract
Traumatic brain injury (TBI) affects an estimated 69 million people each year and remains difficult to diagnose rapidly because conventional assessment relies heavily on neurological examination and computed tomography, which may miss subtle injuries or be unavailable in many clinical settings. Blood-based biomarkers, including S100B, glial fibrillary acidic protein (GFAP), ubiquitin carboxy-terminal hydrolase L1 (UCH-L1), and neurofilament light chain (NfL), provide measurable indicators of glial, neuronal, and axonal injury across different stages of TBI. Nanomaterial-based biosensors have emerged as promising platforms for detecting these biomarkers with high sensitivity, rapid response, and potential for point-of-care testing. This review evaluates recent advances in electrochemical, optical, and emerging biosensor technologies for TBI biomarker detection, with emphasis on analytical performance, clinical validation, and translational potential. The review examines the contributions of gold nanoparticles, graphene derivatives, carbon nanotubes, MXenes, and related nanomaterials to improving signal transduction, surface functionalization, and detection sensitivity in immunosensors and aptasensors. Key analytical parameters, including limit of detection, linear dynamic range, assay time, and selectivity, are assessed against clinically relevant thresholds such as the FDA-cleared GFAP cutoff of 22 pg./mL and the UCH-L1 cutoff of 327 pg./mL. Progress in multiplex biosensing,…
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