Suppr超能文献

基于纳米级钴的金属有机骨架在没有明显一般毒性的情况下损害学习和记忆能力:体内的初步证据。

Nanoscale cobalt-based metal-organic framework impairs learning and memory ability without noticeable general toxicity: First in vivo evidence.

机构信息

State Key Laboratory of Environmental Chemistry and Ecotoxicology, Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing 100085, China; University of Chinese Academy of Sciences, Beijing 100049, China.

State Key Laboratory of Environmental Chemistry and Ecotoxicology, Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing 100085, China.

出版信息

Sci Total Environ. 2021 Jun 1;771:145063. doi: 10.1016/j.scitotenv.2021.145063. Epub 2021 Jan 26.

Abstract

Metal-organic frameworks (MOFs) exhibit broad potential applications in the environmental, biomedical, catalyst, and energy fields. However, the currently existing data hardly shed light on their health risks before the MOFs' large-scale usage. In this context, we exploratively investigated the in vivo fate and effect of one representative cobalt-based zeolitic imidazolate framework (ZIF-67) at the nano- (60 nm) and submicron- (890 nm) scales. Different from submicron-scale ZIF-67 showing better biosafety, nanoscale particles manifested a neurodegenerative risk at the dose of no general toxicity, evidenced by the impairment of learning and memory ability and disordered function of the neuropeptide signaling pathway in a rat model. The involvement of oxidative damage and inflammatory processes in the neurotoxicity induced by ZIF-67 was discussed as well. These findings not only provide a wake-up call for the prudent applications of MOFs but also provide insight into the better design and safer use of MOFs for broader applications.

摘要

金属-有机骨架(MOFs)在环境、生物医学、催化剂和能源等领域具有广泛的应用潜力。然而,在 MOFs 大规模使用之前,目前现有的数据几乎没有揭示它们的健康风险。在这种情况下,我们探索性地研究了一种代表性的钴基沸石咪唑骨架(ZIF-67)在纳米(60nm)和亚微米(890nm)尺度下的体内命运和作用。与亚微米尺度的 ZIF-67 表现出更好的生物安全性不同,纳米颗粒在没有一般毒性的剂量下表现出神经退行性风险,这表现在大鼠模型中学习和记忆能力的损害以及神经肽信号通路的功能紊乱。还讨论了 ZIF-67 诱导的神经毒性中氧化损伤和炎症过程的参与。这些发现不仅为 MOFs 的谨慎应用敲响了警钟,也为更好地设计和更安全地使用 MOFs 以实现更广泛的应用提供了思路。

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验