Electrospun cellulose acetate-doped 3D-graphene nanofibre for enhanced transduction of ochratoxin A determination
Source abstract
Abstract
Ochratoxin A (OTA) is a public health concern because of its carcinogenic, teratogenic and immunotoxic nature, thus sensitive and selective monitoring of this molecule in food samples is of great importance. Herein, we report the development of a highly sensitive and selective electrochemical aptasensor using electrospun cellulose acetate (CA)-doped three-dimensional (3D)-graphene for OTA determination. The free-standing electrospun CA/3D-graphene surface was functionalized with silane and glutaraldehyde functional groups to tether terminal linkers for immobilizing OTA aptamer using the layer-by-layer deposition method. The current–voltage measurements of the proposed aptasensor revealed a low detection limit of 156 fg ml−1 and sensitivity at 0.3 nA with a linear detection range of 1 fg ml−1 to 1 ng ml−1. This aptasensor did not show an interference effect during the selectivity test in the presence of other mycotoxins. The excellent applicability of the developed aptasensor has been verified in paddy rice-spiked samples, showing great potential in fields of food safety. The improved performance of this aptasensor is attributed to the large surface area, interconnected and porous structures of the electrospun fibrous membrane as well as the synergetic effect between graphene and the CA polymeric nanofibres, which creates a suitable matrix for aptamer immobilization and OTA interactions. The proposed aptasensor exhibits excellent sensitivity, selectivity, and thus could be a promising strategy for efficient on-site detection of OTA in food safety control and environmental monitoring.
Source: expertdata · Quality: candidate unverified · Source record ↗
Research context
OpenAlex topics: Mycotoxins in Agriculture and Food · Advanced biosensing and bioanalysis techniques · Analytical chemistry methods development
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
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