Academic Journal

Discriminative detection of glucose and urea with a composite polymer nanofiber based matrix.

Λεπτομέρειες βιβλιογραφικής εγγραφής
Τίτλος: Discriminative detection of glucose and urea with a composite polymer nanofiber based matrix.
Συγγραφείς: Apetrei, Roxana‐Mihaela, Guven, Nese, Camurlu, Pinar
Πηγή: ChemistrySelect; 1/8/2024, Vol. 9 Issue 1, p1-8, 8p
Θεματικοί όροι: Glucose oxidase, Urea, Glucose, Polymers, Patient monitoring, Point-of-care testing
Περίληψη: Detection and quantification of glucose and urea are fundamental in medical analysis, real‐time monitoring, and point of care analysis. However, such analyses generally require sophisticated instrumentation and specialized personnel. Furthermore, discriminative detection of multiple analytes is often necessary for treatment and diagnosis. To address this challenge, this study describes a proof‐of‐concept for discriminative sensitive amperometric detection of both analytes. This was achieved by the fabrication of a polymer‐MWCNTs composite nanofiber matrix upon which glucose oxidase (GOD) and urease were co‐immobilized to allow detection of the corresponding substrates (glucose and urea). The (PAN(−MWCNTs)/Urease‐GOD) biosensor showed good performance in: (i) glucose biosensing with sensitivity of 31±5 μAmM−2cm−2 within an extended linear range (0.1–5.0 mM) and a limit of detection of 3.7 μM, and (ii) urea detection at very low concentration (4–30 and 30–90 μM) with sensitivity up to 350±19 μAmM−2cm−2 and very low LOD (0.1 μM). The analogous mono‐enzyme platform for urea detection (PAN(−MWCNTs)/Urease) showed very similar performance as the bi‐enzyme sensor, suggesting little to no influence of co‐immobilization on Urease activity, thus confirming that the two catalytic processes are independent of each other. The biosensors exhibited high accuracy in the detection of both analytes (at normal and pathological levels) in human serum, thus proving that the biosensor described herein can have practical applications in healthcare and remote patient monitoring. [ABSTRACT FROM AUTHOR]
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