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Although aluminium is one of the most common elements in the biosphere, up to now little is known about its impact on human health. aluminium and its chemical derivatives are highly abundant in food, food contact materials and consumer products. Humans are exposed to aluminium via the gastrointestinal tract (GI tract). Exposition can change substantially due to consumer behavior since aluminium is also a compound of numerous food additives. Recently, aluminium exposition is increasingly considered to cohere with cancer and neurodegenerative disorders. Lately, due to an increasing attentiveness on this topic, limiting values for food additives have been tightened by the EFSA. However, cellular effects of aluminium and especially aluminium-containing nanomaterials, that represent a significant part of chemicals found in food products, are widely unknown and in the focus of our research activities, for example in the bilateral SolNanoTOX project. We established an in vitro simulation system of the GI tract, where nanomaterials undergo the different physiological, chemical and proteinbiochemical conditions of saliva, gastric juice and the intestine. The artificially digested nanomaterials, as well as soluble aluminium chloride as ionic control substance, were subjected to several analytical and biochemical methods to characterize their change of appearance and their cytotoxic effects on intestinal cellular models. We observed the fate of the nanomaterials during typical pH-values of saliva, gastric and intestinal juice with Dynamic light scattering measurements and ICP-MS in the single particle mode. After observable disappearance at pH 2 the particles recovered in the simulated intestinal fluid. The simulation of the GI tract, mainly the change of pH settings, can lead to a certain chemical activation of aluminium that can increase bioavailability in the intestine after oral uptake of aluminium-containing food products. In vitro assays like CTB, MTT and cellular impedance measurements showed that there were no acute cytotoxic effects measurable after a period up to 48h after incubation, comparable to undigested particles. In contrast, high amounts of aluminium ions showed synergistic effects on cell viability compared to non-digested aluminium ions. Although toxicological potential of Al ions to healthy tissue appears to be low, increased hazardous potential cannot be ruled out to pre-damaged tissue and can have a relevance in risk assessment for special consumer groups with for example chronical intestinal inflammation or dietary eating behavior combined with high exposure to Al-containing food products.
Coating, stabilization layers, functionalization of particles or simple contamination are common variants of a core-shell system. For smaller nanoparticles this is of major importance. A particle with 16 nm diameter and a usual surface layer of 2 nm will have the same volume for the core as for the shell. In this case the material of the particle doesn’t have a clear definition. It is a common case that a particle consists of four different layers: Core, shell, stabilization layer and contamination. The properties of the particles differ according to this structure. For example silver particles might have a different dissolution rate for pure particles and for particles which are grown on top of a core.
Different solubility or defined other properties of materials is a common reason for producing core-shell systems. Gold cores are surrounded by silica to stabilize them or to get a defined distance between the cores. Silica might be surrounded by gold and the silica dissolved afterwards. This delivers hollow shells. Another important example for core-shell systems are quantum dots. A small core is surrounded by a different material for increasing the photoluminescence. Furthermore there a stabilization layer is needed. The smallest part of the final particles is the initial core. The photoluminescence is based on this core, but the shells contain much more material. Categorization should address this.
Core-shell systems are not covered by most of the existing decision trees for grouping. They are either regarded as special case or a singular layer. This disqualifies core-shell systems for grouping within the common models. There might be a very easy way to avoid this problem and even to combine some of the different decision trees. Starting the decision tree with the solubility of the outer shell and subsequently addressing the inner layers will be a pragmatic approach to solve the problem. If there is no shell, the categorization can start with a tiered approach or with the proposed “stawman” chemical categorization. If a shell is covering the surface there is a need to check if the shell is stable. If it is stable, the particle can be categorized based on this shell. If it is soluble, the ions need to be addressed as in the classic case. Furthermore the shell might increase the uptake by the cells. If the ions and the uptake are not critical the categorization can continue with the next layer.
With this not perfect but pragmatic approach, the surface layers can be addressed with very limited additional efforts. Most criteria are based on classically tabulated data. Including a rating system like the precautionary matrix approach might even address the fact that some parameters are not always Yes/No, e.g. solubility, ion toxicity and uptake.
Advances in scanning electron microscopy (SEM) enable the high-resolution imaging of single nanoparticles (NPs) with sizes well below 10 nm. The SEM analysis in transmission mode (T-SEM) of NPs on thin film supports has many benefits when compared to the analysis of NPs on bulk substrates. The enhanced material (mass – thickness) contrast of the T-SEM imaging mode is well suited for in-depth and, particularly valuable, to very accurate, traceable, lateral dimensional measurements of NPs. Compared to samples prepared on bulk substrates, T-SEM with energy dispersive X-ray spectroscopy (EDS) achieves a drastically improved spatial resolution of the emitted X-rays. The poor signal-to-noise ratio of the X-ray spectra emitted by a single nanoparticle (NP) can be improved by the use of high-sensitivity (high collection solid angle) silicon drift (SDD), energy-dispersive X-ray spectrometers (EDS). The EDS spectral imaging of a single NP with a spatial resolution below 10 nm has become possible. This is demonstrated by means of various examples of nanostructures. Advanced data processing of T-SEM/EDS results sets the stage for the automated classification of NPs by feature analysis. This method combines the detection of morphological structures of interest by image processing of T-SEM micrographs with the chemical classification by EDS.