4.7 Article

N-acetyl-β-D-glucosaminidase activity assay for monitoring insulin-dependent diabetes using Ag-porous Si SERS platform

期刊

TALANTA
卷 239, 期 -, 页码 -

出版社

ELSEVIER
DOI: 10.1016/j.talanta.2021.123087

关键词

Diabetes; NAG; Optical biosensor; Porous silicon; SERS

资金

  1. JCA Charitable Foundation [459-4610]

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In this study, a modified sensing approach using surface-enhanced Raman spectroscopy (SERS) was proposed for rapid and reliable determination of NAG activity in complex media. The sensitivity of the SERS substrates was evaluated and found to be able to successfully recognize NAG in biological fluids.
Determination of urinary or serum N-acetyl-beta-D-glucosaminidase (NAG) activity as a tissue damage indicator is widely used in diagnosis of various pathologies, including diabetic nephropathy. Early and rapid biomarker detection is an important element of medical diagnosis, facilitating prompt therapeutic decisions and prognosis evaluation. Herein, we present a modified sensing approach for a rapid and reliable NAG activity determination in complex media using surface-enhanced Raman spectroscopy (SERS). Porous silicon (PSi) Fabry-Pe ' rot interferometers were redesigned as sensitive SERS platforms utilizing the vast inherent surface area for silver (Ag) nanoparticles embedment. Interaction of the porous nanostructures with specific NAG-enzymatic products produces an indicative spectral fingerprint proportional in magnitude to its concentration. The sensitivity of Ag-PSi SERS substrates was evaluated in complex matrices presenting sufficient limits of detection compared with other advanced assays and techniques (0.07, 0.47 and 0.50 mU mL(-1) for urine, milk and plasma, respectively). The augmented optical performance revealed recovery values of 96-109%, indicating successful and selective NAG recognition in biological fluids. Finally, the potential applicability of the suggested prototype for real-life scenarios was evaluated in vivo, in a model of insulin-dependent diabetes induced in sheep. Overall, the robust data confirm the application of SERS analysis for early diagnosis of pathology and for evaluation of clinical responses to pharmacological treatments.

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