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Development of an Electrochemical Sensor in a Wound Dressing for the Detection of Chronic Bacterial Infections

Grant number: 25/02774-0
Support Opportunities:Scholarships in Brazil - Scientific Initiation
Start date: May 01, 2025
End date: April 30, 2026
Field of knowledge:Physical Sciences and Mathematics - Chemistry - Analytical Chemistry
Principal Investigator:William Reis de Araujo
Grantee:Kaique Araujo Mendes
Host Institution: Instituto de Química (IQ). Universidade Estadual de Campinas (UNICAMP). Campinas , SP, Brazil
Associated research grant:22/03250-7 - Development of portable and cost-effective biosensors for clinical diagnosis of bacterial and viral infections, AP.PNGP.PI

Abstract

Pseudomonas aeruginosa is one of the most significant pathogens today. It is responsible for various infections and diseases, such as cystic fibrosis, and is a leading cause of hospital-acquired infections. Consequently, it is commonly found in exposed chronic wounds. This project aims to develop a portable and easy-to-use electroanalytical method to assist in identifying and monitoring such infections, particularly in resource-limited settings with high clinical demand and insufficient laboratory infrastructure.To achieve this, wearable electrochemical systems will be integrated into commercial wound dressings using conductive inks and a screen-printing technique. The portable electrochemical sensor will be modified with nanomaterials (graphene derivatives) for the sensitive detection of pyocyanin and pyoverdine, two key biomarkers associated with P. aeruginosa growth. Subsequently, the main analytical parameters will be evaluated, and the method's selectivity will be tested against potential interferents in biological fluids. Finally, the developed device will be applied to simulated biofluid samples (wound exudates) to assess the sensor's accuracy, ensuring its potential for future applications in patient care. This approach aims to reduce the costs associated with traditional sophisticated diagnostics while providing faster and more efficient analyses.

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