Analytical review of nanoplastic bioaccumulation data and a unified toxicokinetic model: from teleosts to human brain

TL;DR

This paper develops a universal, scale-free toxicokinetic model for nanoplastic bioaccumulation, linking experimental data from fish to human brain exposure, highlighting lipid content as a key factor in long-term accumulation.

Contribution

It introduces a unified, analytical toxicokinetic framework that explains nanoplastic accumulation across species and organs, emphasizing lipid-driven partitioning and power-law dependencies.

Findings

Universal trajectory governed by systemic excretion capacity

Organ burdens in humans are consistent with inefficient clearance

Lipid content strongly influences long-term nanoplastic accumulation

Abstract

Nanoplastics (NPs) are increasingly detected in human blood and organs at concentrations reaching hundreds to thousands of parts per million, yet no quantitative framework has linked short-term experimental uptake kinetics to long-term, organ-specific accumulation. Here we analytically review the most reliable uptake and depuration datasets available in teleost fish using a sequential two-compartment toxicokinetic model that distinguishes systemic circulation from tissue-level retention. While anomalous, non-Markovian transport is expected at microscopic scales, we show -- through an explicit theoretic analysis on minimal information -- that such formulations are not identifiable with existing data. Allowing unresolved early-time dynamics to be absorbed into effective, non-zero initial conditions yields an emergent Markovian description that is maximally informative and consistent across species, organs, particle sizes, and exposure levels. When expressed in normalized variables, uptake dynamics collapse onto a universal trajectory governed by a single dimensionless parameter, the systemic excretion capacity, which is generically small under experimental conditions. The resulting scale-free framework reveals systematic power-law dependencies of enrichment and retention times on ambient concentration, particle size, and body mass. Exploiting this structure, we examine the consistency of extrapolations to humans and show that reported organ burdens -- particularly in the brain -- are quantitatively compatible with inefficient systemic clearance and strong lipid-driven partitioning. At steady state, human tissue concentrations follow a robust approximate cubic scaling with lipid fraction, identifying lipid content as the dominant and mechanistically interpretable determinant of chronic nanoplastic accumulation.