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Hyaluronic Acid-Coated Solid Lipid Nanoparticles-Functionalized Quartz-Crystal Microbalance (QCM) Immunosensor for Label-Free Haptoglobin Detection: Toward Monitoring of Neuroinflammation

Journal article 2025

Mariagrazia Lettieri, Luigi Talarico, Giulia Gabbricci, Ilaria Clemente, Simone Pepi, Elia Landi, Ada Fort, Valerio Vignoli, Gabriella Tamasi, Agnese Magnani, Marco Consumi

Analytical Chemistry, 0 (0), 2025

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DOI 10.1021/acs.analchem.5c05079

Abstract

Neurodegenerative diseases (NDs) have distinct molecular mechanisms but share pathological hallmarks, such as dopaminergic neuron degeneration, cognitive decline, and neuroinflammation. These are strongly linked to chronic inflammation and oxidative stress, associated with elevated levels of systemic biomarkers, such as haptoglobin (Hp), an acute-phase inflammatory glycoprotein. However, current Hp detection methods are costly, time-consuming, and insufficiently sensitive, while ND biomarkers require highly invasive cerebrospinal fluid (CSF) sampling. To overcome these limitations, we developed the first quartz-crystal microbalance (QCM)-based immunobiosensor for rapid quantification of human Hp in human serum, offering a less invasive alternative. The system employs a custom QCM-R device for high-resolution frequency/resistance measurements. Fabrication included functionalization of the quartz surface with a thiolated polyethylene glycol amine self-assembled monolayer, followed by immobilization of hyaluronic acid-coated solid lipid nanoparticles (HA-SLNs)─used here for the first time─and covalent attachment of Hp antibodies. The biosensor showed robust performance with high sensitivity (612.10 ± 28.14 μg mL–1), reproducibility (average coefficient of variation, CVav% = 0.50%), selectivity, and excellent limits of detection (0.063 ± 0.003 μg mL–1) and quantification (0.21 ± 0.01 μg mL–1). Surface modifications were validated via time-of-flight secondary ion mass spectrometry (ToF-SIMS), atomic force microscopy (AFM), and electrochemical impedance spectroscopy (EIS). This platform offers a cost-effective, user-friendly alternative for the monitoring of neuroinflammation associated with ND progression by eliminating the need for CSF sampling.

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