.png){kind=icon}
.png){kind=icon}
Return
Thread-Based Bienzymatic Biosensor for Linoleic Acid Detection
.png){kind=icon}
OA
AI
DOI：10.1021/acsomega.4c07394.png)
.png){kind=icon}
.png){kind=icon}
Share.png){kind=icon}
Save
Abstract
En 中文
The concentration of nonesterified fatty acids (NEFAs) in biological media is associated with metabolic and cardiovascular disorders (e.g., diabetes, cancer, and cystic fibrosis) and in food products is indicative of their quality. Therefore, the early identification of NEFAs is crucial for both medical diagnosis and food quality assessment. However, the development of a portable and scalable sensor capable of detecting these compounds at a low cost presents challenges due to their considerable chemical and physical stability. This research endeavors to illustrate the viability of detecting linoleic acid using a chemiresistive bienzymatic sensor constructed with cotton thread. The sensor's design incorporates the conductive polymer poly(3,4-ethylenedioxythiophene):polystyrenesulfonate (PEDOT:PSS) within the thread, alongside the enzymes horseradish peroxidase (HRP) and lipoxygenase (LOX). By implementing this technology, a sensitive detection range spanning from 161 nM to 16.1 mu M is achieved when the PEDOT:PSS/HRP/LOX system is integrated into a single thread. The sensor exhibits exceptional selectivity toward linoleic acid, owing to the specific enzymatic reaction between LOX and linoleic acid. This selectivity is upheld even in the presence of other unsaturated fatty acids. This system can be used for future designs with the capability to detect polyunsaturated fatty acids and other intricate biomolecules.
Keywords:
POLYUNSATURATED FATTY-ACIDS
ELECTROCHEMICAL BIOSENSOR
LIPOXYGENASE
PROFILES
MILK
AI Summary
Key information extracted from the uploaded paper, including a brief overview, abstract, background, key highlights, visual analysis, and future outlook.