Core-shell niobium(v) oxide@molecularly imprinted polythiophene nanoreceptors for transformative, real-time creatinine analysis.
Zohaib SaddiqueMaleeha SaeedMuhammad FaheemSadia Z BajwaAdnan MujahidAdeel AfzalPublished in: Nanoscale advances (2024)
Creatinine, a byproduct of muscle metabolism, is typically filtered by the kidneys. Deviations from normal concentrations of creatinine in human saliva serve as a crucial biomarker for renal diseases. Monitoring these levels becomes particularly essential for individuals undergoing dialysis and those with kidney conditions. This study introduces an innovative disposable point-of-care (PoC) sensor device designed for the prompt detection and continuous monitoring of trace amounts of creatinine. The sensor employs a unique design, featuring a creatinine-imprinted polythiophene matrix combined with niobium oxide nanoparticles. These components are coated onto a screen-printed working electrode. Thorough assessments of creatinine concentrations, spanning from 0 to 1000 nM in a redox solution at pH 7.4 and room temperature, are conducted using cyclic voltammetry (CV), differential pulse voltammetry (DPV), and electrochemical impedance spectroscopy (EIS). The devised sensor exhibits a sensitivity of 4.614 μA cm -2 nM -1 , an impressive trace level limit of detection at 34 pM, and remarkable selectivity for creatinine compared to other analytes found in human saliva, such as glucose, glutamine, urea, tyrosine, etc. Real saliva samples subjected to the sensor reveal a 100% recovery rate. This sensor, characterized by its high sensitivity, cost-effectiveness, selectivity, and reproducibility, holds significant promise for real-time applications in monitoring creatinine levels in individuals with kidney and muscle-related illnesses.
Keyphrases
- uric acid
- room temperature
- molecularly imprinted
- endothelial cells
- skeletal muscle
- metabolic syndrome
- heavy metals
- photodynamic therapy
- high resolution
- blood pressure
- oxide nanoparticles
- gold nanoparticles
- adipose tissue
- solid phase extraction
- machine learning
- induced pluripotent stem cells
- gene expression
- big data
- risk assessment
- mass spectrometry
- sensitive detection
- blood glucose
- polycyclic aromatic hydrocarbons