The transferrin receptor (TfR) is a promising target in cancer therapy owing to its overexpression in most solid tumors and on the blood-brain barrier. Nanostructures chemically derivatized with transferrin are employed in TfR targeting but often lose their functionality upon injection in the bloodstream. As an alternative strategy, we rationally designed a peptide coating able to bind transferrin on suitable pockets not involved in binding to TfR or iron by using an iterative multiscale-modeling approach coupled with quantitative structure-activity and relationship (QSAR) analysis and evolutionary algorithms. We tested that selected sequences have low aspecific protein adsorption and high binding energy toward transferrin, and one of them is efficiently internalized in cells with a transferrin-dependent pathway. Furthermore, it promotes transferrin-mediated endocytosis of gold nanoparticles by modifying their protein corona and promoting oriented adsorption of transferrin. This strategy leads to highly effective nanostructures, potentially useful in diagnostic and therapeutic applications, which exploit (and do not suffer) the protein solvation for achieving a better targeting.
After passage through biological barriers, nanomaterials inevitably end up in contact with the vascular endothelium and can induce cardiovascular damage. In this study the toxicity and sub-lethal effects of six types of nanoparticle, including four of industrial and biomedical importance, on human endothelial cells were investigated using different in vitro assays. The results show that all the particles investigated induce some level of damage to the cells and that silver particles were most toxic, followed by titanium dioxide. Furthermore, endothelial cells were shown to be more susceptible when exposed to silver nanoparticles under flow conditions in a bioreactor. The study underlines that although simple in vitro tests are useful to screen compounds and to identify the type of effect induced on cells, they may not be sufficient to define safe exposure limits. Therefore, once initial toxicity screening has been conducted on nanomaterials, it is necessary to develop more physiologically relevant in vitro models to better understand how nanomaterials can impact on human health.
Intelligent in vitro models able to recapitulate the physiological interactions between tissues in the body have enormous potential as they enable detailed studies on specific two-way or higher order tissue communication. These models are the first step toward building an integrated picture of systemic metabolism and signaling in physiological or pathological conditions. However, the rational design of in vitro models of cell–cell or cell–tissue interaction is difficult as quite often cell culture experiments are driven by the device used, rather than by design considerations. Indeed, very little research has been carried out on in vitro models of metabolism connecting different cell or tissue types in a physiologically and metabolically relevant manner. Here, we analyze the physiological relationship between cells, cell metabolism, and exchange in the human body using allometric rules, downscaling them to an organ-on-a-plate device. In particular, in order to establish appropriate cell ratios in the system in a rational manner, two different allometric scaling models (cell number scaling model and metabolic and surface scaling model) are proposed and applied to a two compartment model of hepatic-vascular metabolic cross-talk. The theoretical scaling studies illustrate that the design and hence relevance of multi-organ models is principally determined by experimental constraints. Two experimentally feasible model configurations are then implemented in a multi-compartment organ-on-a-plate device. An analysis of the metabolic response of the two configurations demonstrates that their glucose and lipid balance is quite different, with only one of the two models recapitulating physiological-like homeostasis. In conclusion, not only do cross-talk and physical stimuli play an important role in in vitro models, but the numeric relationship between cells is also crucial to recreate in vitro interactions, which can be extrapolated to the in vivo reality.
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