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Quantifying the influence of micro and nanoplastics characteristics on cytotoxicity in caco-2 cells through machine learning modelling.
Summary
This systematic review uses machine learning to determine which properties of micro and nanoplastics drive toxicity in human intestinal cell models. The findings reveal that smaller particles and higher concentrations cause more cell damage, which is important for understanding how the microplastics we swallow in food and water might harm our gut lining.
Plastics released into the environment undergo various forms of deterioration, resulting in the formation of micro- and nanoplastics (MNPs). The Caco-2 cell line is commonly used as a model for studying the effects of MNPs on the intestinal epithelial barrier. However, it remains unclear which MNP parameters most significantly impact Caco-2 cytotoxicity. The objective of the study was to identify the major characteristics of MNPs driving the cytotoxicity in Caco-2 cells. A dataset comprising 320 data points was curated through a systematic review, and a random forest model was formulated using MATLAB software. The dataset included 11 features such as MNP type, size, concentration, exposure time and viability tests. Response Ratio (RR) and Log Response Ratio (LnRR) were used as the response variable for individual performance evaluation. Model performance assessment involved a stratified split of the data into 70 Also see: https://micro2024.sciencesconf.org/559589/document