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Optical Interaction Patterns in a Microplastics and Nanoplastics Urine Test: Cross-Donor Consistency of Aged Decentralized Human Urine Samples

Zenodo (CERN European Organization for Nuclear Research) 2026
Melinda Chu

Summary

Researchers are testing a urine-based method to detect microplastics and nanoplastics in people's bodies, which could eventually make it easier to track exposure to these tiny plastic particles without invasive procedures. In this early-stage study, urine samples from three different people—even after sitting for over a week during shipping—showed similar, consistent patterns when analyzed, suggesting the test may work reliably despite real-world handling delays. This is a preliminary finding, not a health verdict: it doesn't yet tell us how much plastic is in your body or what that means for your health, but it's a step toward developing practical tools that could one day help scientists

Human urine represents a promising non-invasive matrix for scalable longitudinal monitoring of environmental microplastic and nanoplastic (MNP) exposure. However, biological matrices introduce substantial variability related to donor chemistry, hydration status, baseline coloration, biochemical composition, and sample aging. These challenges are amplified in decentralized workflows involving real-world shipping and delayed processing. This technical note describes preliminary observations demonstrating cross-donor consistency of concentration-dependent optical interaction morphology in aged decentralized human urine samples evaluated using the EcoExposure™ optical interaction assay. Three independently collected urine samples that underwent approximately 7–10+ days of decentralized storage and shipping prior to processing nevertheless demonstrated recognizable and internally consistent organizational states after standardized assay processing. Importantly, the observed interaction behavior remained conceptually consistent with prior experiments in filtered water, saltwater, and mixed microplastic/nanoplastic systems. These findings support the possibility that transferable interaction-state dynamics may persist across multiple matrices despite substantial biochemical and operational variability.

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