Differential Mapping of Intracellular Metallic Nanoparticles and Ions and Dynamic Modeling Prediction.

Predicting the toxicity of metallic nanoparticles (MNPs) remains a longstanding challenge in the biomedical field, primarily due to the unresolved dynamic transformation between pristine MNPs and their dissolved ionic counterparts within living systems. Herein, we develop an integrative bioimaging-mathematical framework that quantifies, in real-time mode, the contributions of MNPs and their ionic counterparts to toxicity. By integrating aggregation-induced emission (AIE)-based confocal imaging with label-free scattered light tracking, we achieve simultaneous and noninvasive visualization of different-sized pristine silver, copper oxide, and zinc oxide nanoparticles (Ag-, CuO-, and ZnO-NPs, 20-100 nm) and their ionic forms in living cells. This dual-modal approach reveals size-dependent intracellular dissolution dynamics, with 2.68-34.7% of internalized MNPs dissolving post uptake and smaller particles releasing 1.08-1.22 times more ions than larger particles. Leveraging these spatiotemporal insights, we developed a cascading toxicity model that mechanistically links extracellular dissolution, cellular uptake, intracellular transformation, and toxicity pathways. The model demonstrates that ionic species dominate toxicity across all MNPs, contributing 59.7-79.4% (AgNPs), 69.6-100% (CuO-NPs), and 97.7% (ZnO-NPs) of overall toxicity within 0-100 mg/L. Strikingly, toxicity profiles vary by MNP type: AgNPs exhibit biphasic toxicity, CuO-NPs follow a logistic-like pattern, and ZnO-NPs remain entirely ion-driven. By bridging real-time bioimaging with kinetic modeling, our framework provides the first quantitative resolution of nanoparticle- versus ion-specific toxicity. This work not only advances mechanistic understanding of MNP behavior but also establishes a universally applicable tool for predictive nanotoxicology, enabling safer design of nanomaterials and informed regulatory policies.