Abstract：
Nanosized ultrafine particles (UFPs) from natural and anthropogenic sources are widespread and pose serious health risks when inhaled by humans. However, tracing the inhaled UFPs in vivo is extremely difficult, and the distribution, translocation, and metabolism of UFPs remain unclear. Here, we report a label-free, machine learning-aided single-particle inductively coupled plasma mass spectrometry (spICP-MS) approach for tracing the exposure pathways of airborne magnetite nanoparticles (MNPs), including external emission sources, and distribution and translocation in vivo using a mouse model. Our results provide quantitative analysis of different metabolic pathways in mice exposed to MNPs, revealing that the spleen serves as the primary site for MNP metabolism (84.4%), followed by the liver (11.4%). The translocation of inhaled UFPs across different organs alters their particle size. This work provides novel insights into the in vivo fate of UFPs as well as a versatile and powerful platform for nanotoxicology and risk assessment.
摘要：
来自天然和人为来源的纳米超细颗粒（UFP）广泛存在，当被人类吸入时会造成严重的健康风险。然而,在体内追踪吸入的UFP是极其困难的，和分布，易位,UFP的代谢仍不清楚。这里,我们报告一个没有标签的，机器学习辅助的单粒子电感耦合等离子体质谱（spICP-MS）方法，用于追踪空气中磁铁矿纳米粒子（MNPs）的暴露途径，包括外部排放源，以及使用小鼠模型在体内的分布和易位。我们的结果提供了暴露于MNPs的小鼠的不同代谢途径的定量分析，揭示脾脏是MNP代谢的主要部位（84.4%），其次是肝脏（11.4%）。吸入的UFP跨不同器官的易位改变了它们的粒径。这项工作提供了对UFP体内命运的新见解，以及用于纳米毒理学和风险评估的多功能和强大平台。
