人工智能驱动的食品安全:解读肠道微生物群介导的非微生物污染物的健康影响
Ruizhe Xue1, Xinyue Zong1, Xiaoyu Jiang1
1Beijing Key Laboratory of Environmental and Viral Oncology, College of Chemistry and Life Science, Beijing University of Technology, Beijing 100124, China.
Foods (Basel, Switzerland)
|January 10, 2026
概括
非微生物食品污染物影响肠道微生物和宿主健康. 人工智能 (AI) 有助于分析这些复杂的污染物-微生物群-宿主相互作用,以提高食品安全和个性化营养.
科学领域:
- 环境健康 环境健康
- 微生物学 微生物学
- 计算生物学 计算生物学
背景情况:
- 非微生物食品污染物 (重金属,农药,塑料) 影响肠道微生物群和宿主健康.
- 污染物,肠道微生物和健康表型之间的复杂相互作用挑战了传统的分析.
- 人工智能 (AI) 为研究这些关系提供了新的方法.
研究的目的:
- 审查非微生物食品污染物如何改变肠道微生物的组成和功能.
- 探索这些变化的对宿主健康的影响,包括免疫和代谢调节.
- 要突出AI应用在分析污染物-微生物群-宿主相互作用.
主要方法:
- 文献综述综合了当前有关污染物对肠道微生物群的影响的知识.
- 探索人工智能技术 (机器学习,深度学习,网络方法) 用于数据集成.
- 分析AI在识别污染物特征和因果途径方面的作用.
主要成果:
- 非微生物污染物调节肠道微生物群,影响肠道屏障,免疫和新陈代谢.
- 人工智能可以整合多omics和暴露数据,以揭示污染物特定的微生物和代谢物签名.
- 人工智能有助于推断污染物-微生物群-宿主轴中的因果关系路径.
结论:
- 人工智能支持的分析对于理解复杂的污染物-微生物群-宿主相互作用至关重要.
- 未来的工作需要标准化的数据集,可解释的AI和验证管道.
- 人工智能为改善食品安全,精准营养和针对微生物群的干预提供了潜力.
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