Enzyme Nanoparticles 2015
DOI: 10.1016/b978-0-323-38913-6.00006-4
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Applications of Enzyme Nanoparticles

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Cited by 5 publications
(5 citation statements)
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“…Using the DPV method, we were able to show that 3D-NSCAs are superior to the laser-engraved graphene and the carbon nanotubes (CNTs) for UA electrocatalysis, with respect to current density (Figure H), thus establishing the high possibility of 3D-NSCAs as a type of cutting-edge nanoscaled material for developing sensitive sweat, saliva, or urine UA sensor. Through the incorporation of 3D-NSCAs into the sensing module (Figure S17), we obtain a broad linear connection between the UA content and the current with the dynamic ranges of 0.005–0.6 mM and 0.6–4.5 mM and a low detection limit of 1.42 μM (Figure I), which easily overlap the physiological sweat, saliva, and urine UA level ranges . In addition, the UA sensor is also highly selective for typical analytes found in human biofluids (Figure S18).…”
Section: Resultsmentioning
confidence: 95%
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“…Using the DPV method, we were able to show that 3D-NSCAs are superior to the laser-engraved graphene and the carbon nanotubes (CNTs) for UA electrocatalysis, with respect to current density (Figure H), thus establishing the high possibility of 3D-NSCAs as a type of cutting-edge nanoscaled material for developing sensitive sweat, saliva, or urine UA sensor. Through the incorporation of 3D-NSCAs into the sensing module (Figure S17), we obtain a broad linear connection between the UA content and the current with the dynamic ranges of 0.005–0.6 mM and 0.6–4.5 mM and a low detection limit of 1.42 μM (Figure I), which easily overlap the physiological sweat, saliva, and urine UA level ranges . In addition, the UA sensor is also highly selective for typical analytes found in human biofluids (Figure S18).…”
Section: Resultsmentioning
confidence: 95%
“…Through the incorporation of 3D-NSCAs into the sensing module (Figure S17), we obtain a broad linear connection between the UA content and the current with the dynamic ranges of 0.005−0.6 mM and 0.6−4.5 mM and a low detection limit of 1.42 μM (Figure 2I), which easily overlap the physiological sweat, 33 saliva, 31 and urine UA level ranges. 49 In addition, the UA sensor is also highly selective for typical analytes found in human biofluids (Figure S18). Because the UA sensor's response is highly affected by the sweat ionic strength (i.e., Na + level in this study) but not significantly sensitive to the variation of sweat pH (Figures S19 and S20), obtaining a precise evaluation of the raw sweat UA necessitates multiplexed Na + and UA sensing.…”
Section: ■ Results and Discussionmentioning
confidence: 99%
“…In the case of uric acid at a concentration ratio of 1 : 100 (c spe : c inter ) the signal variation exceeded a value of 5 %. By considering the urine level of uric acid in healthy individuals of 3.68 mg dL −1 [44] and the appropriate dilution of the urine sample, it can be concluded that the concentration of uric acid affecting the selectivity of the developed method is three orders of magnitude higher than the expected in the urine sample. By excluding uric acid as a potential interferent, it has been proven that the developed SWV method using ZnONPs‐MWCNTs‐CPE as a sensor is selective for the determination of SPE.…”
Section: Resultsmentioning
confidence: 99%
“… 81 Enzyme-based NPs attracted a lot of attention as biosensors with enhanced analytical performance and showed high potential as nano agents for delivering cargo. 82 , 83 …”
Section: Dye-loaded Protein-based Nanoparticles For Interventional Nimentioning
confidence: 99%
“…81 Enzyme-based NPs attracted a lot of attention as biosensors with enhanced analytical performance and showed high potential as nano agents for delivering cargo. 82,83 Although the above-mentioned types of protein-based NPs did not yet receive enough attention as candidates able to incorporate NIR dyes and serve as NIR fluorescence imaging agents, they display great potential for new research in this field.…”
mentioning
confidence: 99%