Biomimetic smartphone sensor for point-of-care l-dopa monitoring.
- 2026-08
- Talanta 305
- PubMed: 41831337
- DOI: 10.1016/j.talanta.2026.129651
Study Design
- Population
- Parkinson's disease patients
- Methods
- developed a copper-based biomimetic smartphone sensor via one-step electrochemical polymerization of L-Ser, L-His, and copper ions for point-of-care monitoring of l-dopa
- Funding
- Unclear
Point-of-care analysis of levodopa (l-dopa) in patients' blood is crucial yet challenging for the scientific management of Parkinson's disease (PD). In this study, inspired by the catalytic mechanism of tyrosinase, we developed a biomimetic smartphone sensor for point-of-care monitoring of l-dopa. This sensor employs a copper-based biomimetic recognition layer, synthesized via one-step electrochemical polymerization of l-serine (L-Ser), l-histidine (L-His), and copper ions, which forms binuclear copper complexes mimicking the active site of tyrosinase, thereby enabling specific recognition and catalysis of l-dopa. A comprehensive anti-interference analysis was conducted by using 30 potential interferents that may be present in serum. The results confirmed its robust anti-interference performance against coexisting interferents, thereby addressing a significant shortcoming of previous methods. Additionally, the sensor exhibits excellent stability. It maintains stable performance after more than 35 repeated tests. It retains 98.61% of its initial activity after stored at room temperature for one week, effectively reducing analytical costs. Systematic validation experiments confirmed that the constructed copper-based biomimetic sensor exhibits excellent accuracy and precision, with a detection limit as low as 1.32 nM. Integrated with a smartphone via Bluetooth, this sensor enables rapid point-of-care testing of l-dopa, allowing the entire workflow to be completed within 10 min. Its successful application in the analysis of multiple PD patients' serum samples further validates the application potential of the developed biomimetic smartphone sensor in PD population.
Research Insights
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