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A Multi-Matrix Approach to Microplastic and Nanoplastic Detection Across Environmental and Biological Samples
Summary
Researchers proposed a multi-matrix detection framework that applies shared analytical principles for microplastics and nanoplastics across both environmental and biological samples, drawing an analogy to digital pathology where core signal features transfer across contexts while their expression varies with the surrounding matrix.
Detection of microplastics and nanoplastics (MNPs) has traditionally been performed in isolated domains, most commonly environmental water samples or, more recently, human biological matrices such as blood and urine. This technical note outlines a multi-matrix framework in which shared analytical principles can be applied across environmental and biological systems. Initial development in water provides a controlled foundation for extending detection methods to more complex matrices. Conceptually, this approach is analogous to digital pathology, where interpretation relies on recognizing spatial patterns and contextual features rather than isolated signals. In this context, MNP-related signal characteristics may exhibit core, transferable features across matrices, while their expression varies depending on the surrounding environment. This perspective highlights both the continuity of underlying detection principles and the distinct challenges introduced by increasingly complex biological systems.