Salmonella is a major foodborne pathogen that causes salmonellosis, which is characterized by symptoms such as diarrhea, fever, and abdominal cramps. Existing methods for detecting Salmonella, such as culture plating, ELISA, and PCR, are accurate but time-consuming and unsuitable for on-site applications. In this study, we developed a rapid and sensitive electrochemical sensor using a molecularly imprinted polymer (MIP) to detect Salmonella typhimurium (S. typhimurium) by targeting lipopolysaccharides (LPS). Polydopamine (PDA) was used as the polymer matrix because of its cost-efficiency and functional versatility. The sensor demonstrated high sensitivity and selectivity, with a detection limit of 10 CFU/mL and a linear response over the 10²–10⁸ CFU/mL range. The specificity of the sensor was validated against other gram-positive and gram-negative bacteria and showed no significant cross-reactivity. Furthermore, the sensor performed effectively in real food samples, including tap water, milk, and pork, without complex preprocessing. These results highlight the potential of the LPS-imprinted MIP sensor for practical on-site detection of S. typhimurium, improving food safety monitoring and preventing outbreaks in food-handling environments.

Hyungsup Kim, Minwoo Kim and Yongwoo Jang. Biomolecules & Therapeutics 2024;32:192-204. https://doi.org/10.4062/biomolther.2023.118

Self-powered sensor technologies are receiving increasing attention owing to their ability to operate independently without the need for external batteries or power supplies. This autonomy enables continuous and real-time monitoring in various applications. Carbon nanotubes (CNTs) are particularly promising as electrode materials and energy-harvesting components, owing to their excellent electrical conductivity, mechanical robustness, and tunable surface properties. This review provides a concise overview and critical perspectives on recent progress in CNT-based self-powered sensors, focusing on their structural designs, operating mechanisms, and application areas. The sensors are classified according to their practical application environments, including environmental, wearable, and implantable applications, rather than by their energy-harvesting mechanisms or detection targets. Furthermore, current critical challenges, such as durability, scalable fabrication, and in vivo validation, which must be solved to achieve fully autonomous CNT-based sensors for healthcare and environmental monitoring, are discussed. This review underscores the pivotal role of CNT-based self-powered sensors in driving next-generation autonomous monitoring technologies and offers insights for the implementation of such sensors in practical biomedical and environmental applications.