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A broad range of inorganic nanoparticles (NPs) and their dissolved ions possess a possible toxicological risk for human health and the environment. Reliable and robust measurements of dissolution effects may be influenced by the sample matrix, which challenges the analytical method of choice. In this study, CuO NPs were investigated in several dissolution experiments. Two analytical techniques (dynamic light scattering (DLS) and inductively-coupled plasma mass spectrometry (ICP-MS)) were used to characterize NPs (size distribution curves) time-dependently in different complex matrices (e.g., artificial lung lining fluids and cell culture media). The advantages and challenges of each analytical approach are evaluated and discussed. Additionally, a direct-injection single particle (DI sp)ICP-MS technique for assessing the size distribution curve of the dissolved particles was developed and evaluated. The DI technique provides a sensitive response even at low concentrations without any dilution of the complex sample matrix. These experiments were further enhanced with an automated data evaluation procedure to objectively distinguish between ionic and NP events. With this approach, a fast and reproducible determination of inorganic NPs and ionic backgrounds can be achieved. This study can serve as guidance when choosing the optimal analytical method for NP characterization and for the determination of the origin of an adverse effect in NP toxicity.

Due to miscommunication a number of potential co-authors were not listed in the original publication [...]

Whereas the characterization of nanomaterials using different analytical techniques is often highly automated and standardized, the sample preparation that precedes it causes a bottleneck in nanomaterial analysis as it is performed manually. Usually, this pretreatment depends on the skills and experience of the analysts. Furthermore, adequate reporting of the sample preparation is often missing. In this overview, some solutions for techniques widely used in nano-analytics to overcome this problem are discussed. Two examples of sample preparation optimization by automation are presented, which demonstrate that this approach is leading to increased analytical confidence. Our first example is motivated by the need to exclude human bias and focuses on the development of automation in sample introduction. To this end, a robotic system has been developed, which can prepare stable and homogeneous nanomaterial suspensions amenable to a variety of well-established analytical methods, such as dynamic light scattering (DLS), small-angle X-ray scattering (SAXS), field-flow fractionation (FFF) or single-particle inductively coupled mass spectrometry (sp-ICP-MS). Our second example addresses biological samples, such as cells exposed to nanomaterials, which are still challenging for reliable analysis. An air–liquid interface has been developed for the exposure of biological samples to nanomaterial-containing aerosols. The system exposes transmission electron microscopy (TEM) grids under reproducible conditions, whilst also allowing characterization of aerosol composition with mass spectrometry. Such an approach enables correlative measurements combining biological with physicochemical analysis. These case studies demonstrate that standardization and automation of sample preparation setups, combined with appropriate measurement processes and data reduction are crucial steps towards more reliable and reproducible data.

This study focused on immunomodulatory effects of aryl hydrocarbon receptor (AhR) activation through benzo[a]pyrene (BaP) during systemic bacterial infection. Using a well-established mouse model of systemic Salmonella enterica (S.E.) infection, we studied the influence of BaP on the cellular and humoral immune response and the outcome of disease. BaP exposure significantly reduced mortality, which is mainly caused by septic shock. Surprisingly, the bacterial burden in BaP-exposed surviving mice was significantly higher compared to non-exposed mice. During the early phase of infection (days 1–3 post-infection (p.i.)), the transcription of proinflammatory factors (i.e., IL-12, IFN-γ, TNF-α, IL-1β, IL-6, IL-18) was induced faster under BaP exposure. Moreover, BaP supported the activity of antigen-presenting cells (i.e., CD64 (FcγRI), MHC II, NO radicals, phagocytosis) at the site of infection. However, early in infection, the anti-inflammatory cytokines IL-10 and IL-22 were also locally and systemically upregulated in BaP-exposed S.E.-infected mice. BaP-exposure resulted in long-term persistence of salmonellae up to day 90 p.i., which was accompanied by significantly elevated S.E.-specific antibody responses (i.e., IgG1, IgG2c). In summary, these data suggest that BaP-induced AhR activation is capable of preventing a fatal outcome of systemic S.E. infection, but may result in long-term bacterial persistence, which, in turn, may support the development of chronic inflammation.

ACEnano is an EU-funded project which aims at developing, optimising and validating methods for the detection and characterisation of nanomaterials (NMs) in increasingly complex matrices to improve confidence in the results and support their use in regulation. Within this project, several interlaboratory comparisons (ILCs) for the determination of particle size and concentration have been organised to benchmark existing analytical methods. In this paper the results of a number of these ILCs for the characterisation of NMs are presented and discussed. The results of the analyses of pristine well-defined particles such as 60 nm Au NMs in a simple aqueous suspension showed that laboratories are well capable of determining the sizes of these particles. The analysis of particles in complex matrices or formulations such as consumer products resulted in larger variations in particle sizes within technologies and clear differences in capability between techniques. Sunscreen lotion sample analysis by laboratories using spICP-MS and TEM/SEM identified and confirmed the TiO2 particles as being nanoscale and compliant with the EU definition of an NM for regulatory purposes. In a toothpaste sample orthogonal results by PTA, spICP-MS and TEM/SEM agreed and stated the TiO2 particles as not fitting the EU definition of an NM. In general, from the results of these ILCs we conclude that laboratories are well capable of determining particle sizes of NM, even in fairly complex formulations.

Air–liquid interface (ALI) systems have been widely used in recent years to investigate the inhalation toxicity of many gaseous compounds, chemicals, and nanomaterials and represent an emerging and promising in vitro method to supplement in vivo studies. ALI exposure reflects the physiological conditions of the deep lung more closely to subacute in vivo inhalation scenarios compared to submerged exposure. The comparability of the toxicological results obtained from in vivo and in vitro inhalation data is still challenging. The robustness of ALI exposure scenarios is not yet well understood, but critical for the potential standardization of these methods. We report a cause-and-effect (C&E) analysis of a flow through ALI exposure system. The influence of five different instrumental and physiological parameters affecting cell viability and exposure parameters of a human lung cell line in vitro (exposure duration, relative humidity, temperature, CO2 concentration and flow rate) was investigated. After exposing lung epithelia cells to a CeO2 nanoparticle (NP) aerosol, intracellular CeO2 concentrations reached values similar to those found in a recent subacute rat inhalation study in vivo. This is the first study showing that the NP concentration reached in vitro using a flow through ALI system were the same as those in an in vivo study.

Single cell imaging mass spectrometry opens up a complete new perspective for strategies in toxicological risk assessment and drug discovery. In particular, time-of-flight secondary ion mass spectrometry (ToF-SIMS) with its high spatial and depth resolution is becoming part of the imaging mass spectrometry toolbox used for single cell analysis. Recent instrumentation advancements in combination with newly developed cluster ion guns allow 3-dimensional reconstruction of single cells together with a spatially resolved compound location and quantification on nanoscale depth level. The exact location and quantification of a single compound or even of a set of compounds is no longer restricted to the two dimensional space within single cells, but is available for voxels, a cube-sized 3-dimensional space, rather than pixels. The information gathered from one voxel is further analysed using multivariate statistical methodology like maximum autocorrelation factors to co-locate the compounds of interest within intracellular organelles like nucleus, mitochondria or golgi apparatus. Furthermore, the cell membrane may be resolved, including adhering compounds and potential changes of the lipid patterns. The generated information can be used further for a first evaluation of intracellular target specifity of new drug candidates or for the toxicological risk assessment of environmental chemicals and their intracellular metabolites. Additionally, single cell lipidomics and metabolomics enable for the first time an in-depth understanding of the activation or inhibition of cellular biosynthesis and signalling pathways.