Novel MoS 2 -decorated Cu 2 O hybrid nanoparticles for enhanced non-enzymatic electrochemical cholesterol detection.
Janani K MAshok Kumar LAlagappan MPublished in: Nanotechnology (2024)
Precise identification of cholesterol levels is crucial for the early diagnosis of cardiovascular risk factors. This paper presents a novel approach for cholesterol detection that circumvents the reliance on enzymatic processes. Leveraging the unique properties of advanced materials and electrochemical principles, our non-enzymatic approach demonstrates enhanced sensitivity, specificity, and limit of detection in cholesterol analysis. A non-enzymatic electrochemical biosensor for Cholesterol, employing a nanohybrid comprising Cu 2 O nanoparticles decorated with MoS 2 , is presented. The cyclic voltammetry (CV), differential pulse voltammetry (DPV), and amperometry techniques were employed to investigate the electrochemical behaviour of the glassy carbon electrode modified with the Cu 2 O/MoS 2 nanohybrid. The modified electrode exhibited an excellent sensitivity of 111.74 μ A μ M -1 cm -2 through the CV method and showcased a low detection limit of 2.18 μ M and an expansive linear range spanning 0.1-180 μ M when employing the DPV method. The electrode also showed good selectivity to various interfering components in 0.1 M NaOH and a satisfied stability of about 15 days at room temperature. The study demonstrates the potential for broader applications in clinical diagnostics and monitoring cardiovascular health, paving the way for a paradigm shift in cholesterol detection methodologies and offering a more efficient and cost-effective alternative to traditional enzymatic assays.
Keyphrases
- label free
- room temperature
- gold nanoparticles
- reduced graphene oxide
- low density lipoprotein
- quantum dots
- ionic liquid
- loop mediated isothermal amplification
- hydrogen peroxide
- cardiovascular risk factors
- real time pcr
- blood pressure
- molecularly imprinted
- metabolic syndrome
- highly efficient
- high throughput
- risk assessment
- type diabetes
- sensitive detection
- metal organic framework
- nitric oxide
- single cell
- high resolution
- electron transfer
- solid state
- tandem mass spectrometry
- bioinformatics analysis