Advancing understanding of microbial biofilms through machine learning-powered studies

被引:0
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作者
Ting Liu
Yuting Zhai
Kwangcheol Casey Jeong
机构
[1] University of Florida,Emerging Pathogens Institute
[2] University of Florida,Department of Animal Sciences
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关键词
Microbial biofilms; Food; Food industry; Public health; Machine learning;
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摘要
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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页码:1653 / 1664
页数:11
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