Silver nanoparticles in complex biological media: assessment of colloidal stability and protein corona formation
Source abstract
Abstract
Engineered silver nanoparticles (AgNPs) are among the most used nanomaterials in consumer products, therefore concerns are raised about their potential for adverse effects in humans and environment. Although an increasing number of studies in vitro and in vivo are being reported on the toxicity of AgNPs, most of them suffer from incomplete characterization of AgNPs in the tested biological media. As a consequence, the comparison of toxicological data is troublesome and the toxicity evaluation still remains an open critical issue. The development of a reliable protocol to evaluate interactions of AgNPs with surrounding proteins as well as to assess their colloidal stability is therefore required. In this regard, it is of importance not only to use multiple, easy-to-access and simple techniques but also to understand limitations of each characterization methods. In this work, the morphological and structural behaviour of AgNPs has been studied in two relevant biological media, namely 10 % FBS and MP. Three different techniques (Dynamic Light Scattering, Transmission Electron Microscopy, UV–Vis spectroscopy) were tested for their suitability in detecting AgNPs of three different sizes (10, 40 and 100 nm) coated with either citrate or polyvinylpyrrolidone. Results showed that UV–Vis spectroscopy is the most versatile and informative technique to gain information about interaction between AgNPs and surrounding proteins and to determine their colloidal stability in the tested biological media. These findings are expected to provide useful insights in characterizing AgNPs before performing any further in vitro/in vivo experiment.
Source: openaire · Quality: candidate unverified · Source record ↗
Research context
OpenAlex topics: Nanoparticles: synthesis and applications · Gold and Silver Nanoparticles Synthesis and Applications
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
References (54)
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