Nanoparticles in bodily tissues: predicting their equilibrium distributions. Issue 2 (11th January 2023)

• Record Type: Journal Article
• Authors: Nolte, Tom M.; Lu, Bingqing; Hendriks, A. Jan
• Is Part Of: Environmental science. Volume 10:Issue 2(2023)
• Page Start: 424
• Page End: 439
• Publication Date: 2023-01-11
• Subjects: Environmental sciences -- Periodicals; Nanotechnology -- Periodicals; 620.505
• DOI: 10.1039/d2en00469k
• Languages: English
• ISSNs: 2051-8153

Abstract

Abstract : We successfully predict distribution of nanoparticles (NPs) in human tissues applying surface energies for NPs, membranes, plasma and protein, considering various biochemical interactions. Phagocyte-rich and cancerous tissues accumulate NPs. Abstract : Nanoparticles (NPs) interact within organisms via various biochemical interactions which can bring benefits to society. Classically, fate/distribution of substances is assessed via phase (octanol–water) based partitioning. A decade ago, Praetorius famously stated that phase-based partitioning for NPs is "a road to nowhere". While ( in vivo ) experiments are cumbersome, reliable partitioning values are of utmost importance given a wealth of medicinal/toxicological and environmental exposure assessments. In this communication, we describe calculus for distribution in human tissues. We applied surface free energy components for NPs, cell membranes/vesicles, plasma and protein describing (van de Waals and Lewis acid–base) interactions amongst tissue and blood constituents. We considered neutral and charged NPs, and various tissues for statistical evaluation. Comparison to experiments showed that predictions are acceptable ( R 2 ≥ 0.7). Depending on surface functionality, phagocyte-rich and cancerous tissues accumulate NPs distinctly from 'normal' tissue, via e.g., receptor (lectin/cadherin) binding. Our modeling study aids and supplements experiments to quantify the interactions, tissues concentrations and transport of NPs with(in) organs, to unravel mechanisms of human exposures. It provides a reference for partitioning to benchmark upcoming medical applications ( e.g., PBPK) and human/ecological risk assessments, enabling experimentalists more efficient monitoring, data interpretation, and reduces cost/time-intensive medicinal and toxicological campaigns.