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Detection of Microplastics and Nanoplastics in Blood-Relevant Matrices for Scalable Routine Testing
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A scalable, non-destructive optical imaging workflow successfully detected microplastics and nanoplastics in simulated blood matrices, with nanoplastics showing distinct aggregation patterns even at low concentrations. This approach could enable routine clinical monitoring of systemic plastic burden, which is essential given that circulating particles may interact with immune, vascular, and neurological systems.
Abstract Microplastics and nanoplastics (MNPs) have been detected in human blood and other tissues, raising concerns about systemic exposure and potential health effects. However, current analytical approaches remain limited by cost, scalability, and incompatibility with complex biological matrices, particularly for nanoplastics. Blood represents a clinically relevant matrix for evaluating systemic exposure, as circulating particles may interact with immune, vascular, and neurological systems. In this report, simulated blood matrices were evaluated across microplastic and nanoplastic conditions using standardized optical imaging and computational analysis. Samples were prepared under controlled conditions and assessed at defined timepoints using a non-destructive imaging workflow. Reproducible differences in optical structure (spatial heterogeneity, aggregation behavior, and temporal evolution) were observed, with nanoplastic conditions demonstrating earlier and more pronounced organization at low concentrations. Computational analysis focused on emergent optical patterns rather than direct particle counting enables detection of both micro- and nanoplastic-associated signals in intact liquid samples. These results demonstrate feasibility of a scalable, non-destructive framework for assessing systemic MNP burden and support future integration into routine monitoring and longitudinal studies. Keywords: microplastics, nanoplastics, blood, optical imaging, scalable detection, biomonitoring
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Detection of Microplastics and Nanoplastics in Blood-Relevant Matrices for Scalable Routine Testing
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Using optical imaging and computational analysis of simulated blood matrices, researchers demonstrated a scalable, non-destructive method capable of distinguishing microplastic and nanoplastic contamination conditions, with nanoplastics showing earlier and more pronounced optical signatures. This framework could enable routine blood-based monitoring of systemic MNP exposure without the cost and complexity of current analytical methods.
Toward Scalable Detection of Microplastics and Nanoplastics in Human Biological Systems: Alignment with STOMP Objectives and Preliminary Feasibility Data
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This preliminary study described a non-destructive, image-based optical framework that detects microplastics and nanoplastics in intact biofluids such as urine and blood without sample destruction, showing reproducible spatial and temporal signal patterns in spiked matrices. The authors proposed this approach as a pathway toward scalable, high-throughput monitoring of human microplastic exposure aligned with the ARPA-H STOMP program objectives.
Toward Scalable Detection of Microplastics and Nanoplastics in Human Biological Systems: Alignment with STOMP Objectives and Preliminary Feasibility Data
AI summary Read the abstract
This preliminary study described a non-destructive, image-based optical framework that detects microplastics and nanoplastics in intact biofluids such as urine and blood without sample destruction, showing reproducible spatial and temporal signal patterns in spiked matrices. The authors proposed this approach as a pathway toward scalable, high-throughput monitoring of human microplastic exposure aligned with the ARPA-H STOMP program objectives.
Preliminary Report: Scalable Detection of Microplastics and Nanoplastics in Human Urine
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A non-destructive optical imaging workflow successfully detected both micro- and nanoplastic signals in spiked human urine, showing reproducible differences in spatial heterogeneity and aggregation behavior at varying concentrations. This scalable, non-invasive detection method could enable routine biomonitoring of human plastic exposure through urine sampling.
Preliminary Report: Scalable Detection of Microplastics and Nanoplastics in Human Urine
AI summary Read the abstract
A preliminary study validated a non-destructive optical imaging workflow for detecting both micro- and nanoplastics in spiked human urine samples, observing reproducible differences in particle aggregation and spatial organization between microplastic and nanoplastic conditions at low concentrations. A scalable, non-invasive urine-based detection method would transform biomonitoring capacity, enabling population-level tracking of internal microplastic exposure without the invasive sampling currently required.
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