Advancing understanding of microbial biofilms through machine learning-powered studies

利用机器学习研究增进对微生物生物膜的理解

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Abstract

Microbial biofilms are prevalent in various environments and pose significant challenges to food safety and public health. The biofilms formed by pathogens can cause food spoilage, foodborne illness, and infectious diseases, which are difficult to treat due to their enhanced antimicrobial resistance. While the composition and development of biofilms have been widely studied, their profound impact on food, the food industry, and public health has not been sufficiently recapitulated. This review aims to provide a comprehensive overview of microbial biofilms in the food industry and their implication on public health. It highlights the existence of biofilms along the food-producing chains and the underlying mechanisms of biofilm-associated diseases. Furthermore, this review thoroughly summarizes the enhanced understanding of microbial biofilms achieved through machine learning approaches in biofilm research. By consolidating existing knowledge, this review intends to facilitate developing effective strategies to combat biofilm-associated infections in both the food industry and public health.

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