Objective
Nanoplastics (NPLs) are one of the most hazardous emerging environmental pollutants. We nevertheless still have a limited understanding of the precise toxicological mechanisms in living organisms. Herein, we propose a miniaturized electrochemical sensing platform combined with single-cell techniques to simultaneously and dynamically monitor the concentration of NPLs ingested by a single cell that is actually causing adverse effect and the release of toxicological markers (such as H2O2, H2S or specific DNA/RNA) from cellular damage. The implementation of this project is based on the innovation of the preparation technology of carbon-based microelectrodes functionalized with alkyl chain monolayer and recognition sites, which for the first time will be simultaneously integrated with single-cell analytical techniques for environmental risk assessment. Investigating the toxicology of NPLs at the single-cell level can avoid obtaining only the average expression of a population of cells and ignoring intracellular heterogeneity. Meanwhile, the toxicological concentration of NPLs and the type and concentration of toxicological markers will be efficiently matched, screened and quantified using machine learning, which can provide a phased and hierarchical understanding of the mechanism of toxicity evolution of NPLs in individual cells, and thus provide accurate references for the prediction of and early warning on the toxic effects of NPLs on living organisms. The development of this interdisciplinary technique is expected to not only broaden the understanding of the hazards of NPLs and reveal the evolutionary process of toxicity caused by NPLs, but will also provide an analytical platform for toxicological assessment of other types of pollutants. Moreover, it is promising to promote the commercialization of a portable device for the rapid detection of NPLs in water samples, which will provide a powerful tool for environmental protection and household water quality monitoring.
Fields of science (EuroSciVoc)
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques.
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques.
- natural sciencesbiological sciencesgeneticsDNA
- natural sciencesbiological sciencesgeneticsRNA
- medical and health sciencesbasic medicinetoxicology
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Keywords
Programme(s)
- HORIZON.1.2 - Marie Skłodowska-Curie Actions (MSCA) Main Programme
Funding Scheme
HORIZON-TMA-MSCA-PF-EF - HORIZON TMA MSCA Postdoctoral Fellowships - European FellowshipsCoordinator
2311 EZ Leiden
Netherlands