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    Glial-fibrillary-acidic-protein (GFAP) biomarker detection in serum-matrix: Functionalization strategies and detection by an ultra-high-frequency surface-acoustic-wave (UHF-SAW) lab-on-chip

    Year: 2021

    Journal: Biosens. Bioelectron., Volume 172, JAN 15

    Authors: Agostini, M.; Amato, F.; Vieri, M. L.; Greco, G.; Tonazzini, I.; Baroncelli, L.; Caleo, M.; Vannini, E.; Santi, M.; Signore, G.; Cecchini, M.

    Keywords: Biosensor; Lab-on-chip; Quartz crystal microbalance (QCM); Surface acoustic wave (SAW); Glial fibrillary acidic protein (GFAP); Brain damage; Point of care

    Glial-fibrillary-acidic-protein (GFAP) has recently drawn significant attention from the clinical environment as a promising biomarker. The pathologies which can be linked to the presence of GFAP in blood severely affect the human central nervous system. These pathologies are glioblastoma multiforme (GBM), traumatic brain injuries (TBIs), multiple sclerosis (MS), intracerebral hemorrhage (ICH), and neuromyelitis optica (NMO). Here, we develop three different detection strategies for GFAP, among the most popular in the biosensing field and never examined side by side within the experimental frame. We compare their capability of detecting GFAP in a clean buffer and serum-matrix by using gold-coated quartz-crystal-microbalance (QCM) sensors. All the three detection strategies are based on antibodies, and each of them focuses on a key aspect of the biosensing process. The first is based on a polyethylene glycol (PEG) chain for antifouling, the second on a protein-G linker for controlling antibody-orientation, and the third on antibody-splitting and direct surface immobilization for high-surface coverage. Then, we select the best-performing protocol and validate its detection performance with an ultrahigh-frequency (UHF) surface-acoustic-wave (SAW) based lab-on-chip (LoC). GFAP successful detection is demonstrated in a clean-buffer and serum-matrix at a concentration of 35 pM. This GFAP level is compatible with clinical diagnostics. This result suggests the use of our technology for the realization of a point-of-care biosensing platform for the detection of multiple brain-pathology biomarkers.
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