The dispersion method does not affect the in vitro genotoxicity of multi-walled carbon nanotubes despite inducing surface alterations.

Multi-walled carbon nanotubes (MWCNTs) are a desirable class of high aspect ratio nanomaterials (HARNs) owing to their extensive applications. Given their demand, the growing occupational and consumer exposure to these materials has warranted an extensive investigation into potential hazards they may pose towards human health. This study utilised both the in vitro mammalian cell gene mutation and the cytokinesis-blocked micronucleus (CBMN) assays to investigate genotoxicity in human lymphoblastoid (TK6) and 16HBE14o human lung epithelial cells, following exposure to NM-400 and NM-401 MWCNTs for 24 h.

Cell-nanoparticle stickiness and dose delivery in a multi-model in silico platform: DosiGUI.

Background: It is well-known that nanoparticles sediment, diffuse and aggregate when dispersed in a fluid. Once they approach a cell monolayer, depending on the affinity or "stickiness" between cells and nanoparticles, they may adsorb instantaneously, settle slowly - in a time- and concentration-dependent manner - or even encounter steric hindrance and rebound. Therefore, the dose perceived by cells in culture may not necessarily be that initially administered.

Design rules applied to silver nanoparticles synthesis: A practical example of machine learning application.

The synthesis of silver nanoparticles with controlled physicochemical properties is essential for governing their intended functionalities and safety profiles. However, synthesis process involves multiple parameters that could influence the resulting properties. This challenge could be addressed with the development of predictive models that forecast endpoints based on key synthesis parameters.

Dosimetry - exploring the sensitivity of deposited dose predictions vs. affinity, polydispersity, freeze-thawing, and analytical methods.

Dose-response by testing is only valid if the fraction of the particle dose that deposits onto adherent cells is known. Modeling tools such as the 'distorted grid' (DG) code are common practices to predict that fraction. As another challenge, workflow efficiency depends on parallelized sample preparation, for which freeze-thaw protocols have been explored earlier, but not their implications on dosimetry.