挑战与机遇:医疗器械表面应用中的传染病与抗菌素耐药性之间的相互作用
Valerie Ortiz-Gómez1,2, Rafael Maldonado-Hernández2,3
1Department of Natural Sciences and Technology, Ana G. Méndez University, Gurabo Campus, Gurabo, Puerto Rico 00777, United States.
ACS omega
|June 9, 2025
概括
人工智能 (AI) 加快了抗微生物 (AMP) 和生物活性表面的发现,以对抗多药耐药性感染. 这些由人工智能驱动的策略为预防与设备相关的感染和解决抗菌素耐药性 (AMR) 提供了新的解决方案.
科学领域:
- 综合生物科学是一个整体的生物科学.
- 计算生物学是一种计算生物学.
- 材料科学是一种材料科学.
背景情况:
- 抗菌素耐药性 (AMR) 是一个全球性的健康危机,由与医疗器械相关的多药耐药性感染加剧.
- 现有的抗微生物策略是不够的,需要新的方法来对抗设备相关的感染.
研究的目的:
- 审查人工智能 (AI) 在发现抗微生物 (AMP) 和设计生物活性表面方面的整合.
- 探索人工智能驱动的策略,以减轻与设备相关的感染,并应对AMR大流行.
主要方法:
- 基于人工智能的模型,用于加速识别和优化具有抗菌膜活性的抗微生物.
- 复习先进的表面工程技术:仿生涂层,质量检测抑制剂和基于酶的策略.
- 统一的视角整合了计算预测,材料科学和微生物病原学.
主要成果:
- 人工智能显著提高了强大的抗微生物的发现和优化.
- 表面工程创新有效地破坏了医疗器械上的细菌殖民和生物膜形成.
- 结合人工智能和先进材料的混合策略对下一代抗菌表面显示出希望.
结论:
- 人工智能辅助方法为开发新型抗微生物和表面提供了强大的工具包.
- 先进的表面修饰对于防止生物膜形成和与设备相关的感染至关重要.
- 这种综合方法在医疗保健环境中对抗抗菌素耐药性具有重大潜力.
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