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A Hybrid Perfusion-Diffusion based PBK model for the distribution of nano- and microplastics in the human body

Zenodo (CERN European Organization for Nuclear Research) 2024 Score: 45 ? 0–100 AI score estimating relevance to the microplastics field. Papers below 30 are filtered from public browse.
Ira Wardani, Koelmans Albert A., Ira Wardani, Nur Hazimah Mohamed Nor, Nur Hazimah Mohamed Nor, Ira Wardani, Ira Wardani, Merel Kooi Nur Hazimah Mohamed Nor, Nur Hazimah Mohamed Nor, Ira Wardani, Ira Wardani, Koelmans Albert A., Nur Hazimah Mohamed Nor, Nur Hazimah Mohamed Nor, Ira Wardani, Nur Hazimah Mohamed Nor, Nur Hazimah Mohamed Nor, Nur Hazimah Mohamed Nor, Nur Hazimah Mohamed Nor, Nur Hazimah Mohamed Nor, Merel Kooi Merel Kooi Merel Kooi Merel Kooi Merel Kooi Merel Kooi Ira Wardani, Merel Kooi Nur Hazimah Mohamed Nor, Merel Kooi, Merel Kooi, Merel Kooi, Merel Kooi, Merel Kooi, Merel Kooi, Nur Hazimah Mohamed Nor, Nur Hazimah Mohamed Nor, Merel Kooi Merel Kooi Koelmans Albert A., Merel Kooi, Merel Kooi, Koelmans Albert A., Nur Hazimah Mohamed Nor, Koelmans Albert A., Koelmans Albert A., Koelmans Albert A., Merel Kooi, Nur Hazimah Mohamed Nor, Nur Hazimah Mohamed Nor, Merel Kooi, Nur Hazimah Mohamed Nor, Koelmans Albert A., Nur Hazimah Mohamed Nor, Koelmans Albert A., Merel Kooi Merel Kooi Koelmans Albert A., Merel Kooi Ira Wardani, Koelmans Albert A., Koelmans Albert A., Ira Wardani, Koelmans Albert A., Ira Wardani, Merel Kooi Ira Wardani, Koelmans Albert A., Koelmans Albert A., Koelmans Albert A., Ira Wardani, Ira Wardani, Nur Hazimah Mohamed Nor, Koelmans Albert A., Koelmans Albert A., Koelmans Albert A., Koelmans Albert A., Koelmans Albert A., Koelmans Albert A., Koelmans Albert A., Koelmans Albert A., Ira Wardani, Ira Wardani, Ira Wardani, Ira Wardani, Ira Wardani, Ira Wardani, Koelmans Albert A., Koelmans Albert A., Koelmans Albert A., Merel Kooi Koelmans Albert A., Merel Kooi, Koelmans Albert A., Merel Kooi Koelmans Albert A., Koelmans Albert A., Koelmans Albert A., Merel Kooi, Nur Hazimah Mohamed Nor, Ira Wardani, Ira Wardani, Koelmans Albert A., Koelmans Albert A., Merel Kooi

Summary

Researchers developed a hybrid physiologically-based kinetic model to predict the distribution of nano- and microplastic particles in the human body after ingestion. The model integrates perfusion and diffusion processes to estimate tissue-specific particle concentrations across different exposure scenarios.

Body Systems

The widespread occurrence of nano- and microplastic particles (NMPs) in environmental matrices has prompted concerns about their potential implications for human health. Despite extensive research efforts, the true risk posed by NMPs remains unclear, primarily due to challenges in conducting comprehensive risk assessments. One significant obstacle comes from the disparity between experimental studies, often employing monodisperse NMP particles, and real-life exposure scenarios where humans encounter polydisperse NMPs with diverse chemical characteristics. To address this gap, we propose a novel approach that integrates probabilistic approaches with a Hybrid Perfusion and Diffusion Physiologically Based Kinetic (HPD-PBK) model to elucidate the bioaccumulation and biokinetics of NMP in the human body. The new hybrid perfusion-diffusion concept suggests that there is a particle-size-based probability that NMP kinetics will either follow perfusion or diffusion-based transport limitations within the PBK model. This approach encompasses the entire spectrum of NMP particles, ranging from 10 nm to 5000 µm. The model was applied for scenarios involving monodisperse versus polydisperse NMP particles, further enhancing its applicability to real-world exposure scenarios. We established a tiered approach for selecting model parameters and optimizations, guided by assessment criteria from previous studies. Validation of our model is achieved through an alignment with empirical human data on NMP body burdens across various organs. Our findings yield a conceptual probabilistic model that accounts for the inherent diversity of NMP particles from inhalation and dietary exposure, and the variability in human physiologies. While our model represents a significant advancement, further data collection efforts are essential to refine model parameters and enhance the representativeness of the human PBK model for NMPs. This integrated approach offers valuable insights for informing future comprehensive risk assessments and mitigating potential health risks associated with NMP exposure. Also see: https://micro2024.sciencesconf.org/558426/document

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