Nanomedicine utilizes the remarkable properties of nanomaterials for the diagnosis, treatment, and prevention of disease.

To fully understand the potential ecological and human health risks from nanoplastics and microplastics (NMPs) in the environment, it is critical to make accurate measurements. Similar to past research on the toxicology of engineered nanomaterials, a broad range of measurement artifacts and biases are possible when testing their potential toxicity. For example, antimicrobials and surfactants may be present in commercially available NMP dispersions, and these compounds may account for toxicity observed instead of being caused by exposure to the NMP particles. Therefore, control measurements are needed to assess potential artifacts, and revisions to the protocol may be needed to eliminate or reduce the artifacts. In this paper, we comprehensively review and suggest a next generation of control experiments to identify measurement artifacts and biases that can occur while performing NMP toxicity experiments. This review covers the broad range of potential NMP toxicological experiments, such as in vitro studies with a single cell type or complex 3-D tissue constructs, in vivo mammalian studies, and ecotoxicity experiments testing pelagic, sediment, and soil organisms. Incorporation of these control experiments can reduce the likelihood of false positive and false negative results and more accurately elucidate the potential ecological and human health risks of NMPs.

In single particle inductively coupled plasma mass spectrometry (spICP-MS), the transport efficiency is fundamental for the correct determination of both particle number concentration and size. In the present study, transport efficiency was systematically determined on three different days with six carefully characterised gold nanoparticle (AuNP) suspensions and in seven European and US expert laboratories using different ICP-MS instruments and spICP-MS software. Both particle size—(TES)—and particle frequency—(TEF)—methods were applied. The resulting transport efficiencies did not deviate much under ideal conditions. The TEF method however systematically resulted in lower transport efficiencies. The extent of this difference (0–300% rel. difference) depended largely on the choice and storage conditions of the nanoparticle suspensions used for the determination. The TES method is recommended when the principal measurement objective is particle size. If the main aim of the measurement is the determination of the particle number concentration, the TEF approach could be preferred as it might better account for particle losses in the sample introduction system.

Due to enhanced properties at the nanoscale, nanomaterials (NMs) have been incorporated into foods, food additives, and food packaging materials. Knowledge gaps related to (but not limited to) fate, transport, bioaccumulation, and toxicity of nanomaterials have led to an expedient need to expand research efforts in the food research field. While classical techniques can provide information on dilute suspensions, these techniques sample a low throughput of nanoparticles (NPs) in the suspension and are limited in the range of the measurement metrics so orthogonal techniques must be used in tandem to fill in measurement gaps. New and innovative characterization techniques have been developed and optimized for employment in food nano-characterization. Single particle inductively coupled plasma mass spectrometry, a high-throughput nanoparticle characterization technique capable of providing vital measurands of NP-containing samples such as size distribution, number concentration, and NP evolution has been employed as a characterization technique in food research since its inception. Here, we offer a short, critical review highlighting existing studies that employ spICP-MS in food research with a particular focus on method validation and trends in sample preparation and spICP-MS methodology. Importantly, we identify and address areas in research as well as offer insights into yet to be addressed knowledge gaps in methodology.

Particle number concentration (PNC) measurements are critical for research and regulatory decision making related to the potential applications and implications of nanotechnology. However, the degree to which different analytical methods yield similar PNCs has not yet been studied. In this study, monodisperse gold nanoparticles (AuNPs) with varying sizes (30 nm or 60 nm) and surface coatings (citrate, polyvinylpyrrolidone, or branched polyethyleneimine) were evaluated using five techniques: scanning electron microscopy (SEM), dynamic light scattering (DLS), differential mobility analysis (DMA), nanoparticle tracking analysis (NTA), and single particle inductively coupled plasma-mass spectrometry (spICP-MS). The two techniques that only measured the NP core size (spICP-MS and SEM), as opposed to the larger hydrodynamic diameter, yielded PNCs with the closest agreement (within 20% of each other), while PNCs among all techniques sometimes varied by a factor of 3. Positively charged AuNPs coated with branched polyethyleneimine yielded the most variable results. Deriving the PNC using the particle size distribution has several advantages over using only the mean size based on these results and statistical modeling given the substantial impact of the tails of the distribution toward smaller particles. The size distributions measured by the different techniques were also used to model the AuNP concentration that would reach the cells in an in vitro toxicity experiment. Surprisingly, there was a strong impact of the analytical technique on the modeled cellular AuNP concentration for some of the AuNPs.