Sunscreens containing metal oxide nanoparticles appear transparent on the skin and provide excellent protection against sunburn caused by UV radiation. While it is likely that nanoparticles remain on the surface of the skin of healthy adult humans, and thus are considered safe for use in sunscreens, there has been no comprehensive assessment of the impact on human health from exposure to the metal oxide nanoparticles destined for use in sunscreens, either in the workplace during the manufacturing process, in long-term use across a range of skin conditions, or upon release into the broader environment, either accidentally or consequent of normal sunscreen use. In this review, we focus on zinc oxide nanoparticles destined for use in modern sunscreens, and discuss the potential for human exposure and the health hazard at each stage of their manufacture and use. We highlight where there is a need for further research.

It has been suggested that carbon nanotubes might conform to the fibre pathogenicity paradigm that explains the toxicities of asbestos and other fibres on a continuum based on length, aspect ratio and biopersistence. Some types of carbon nanotubes satisfy the first two aspects of the fibre paradigm but only recently has their biopersistence begun to be investigated. Biopersistence is complex and requires in vivo testing and analysis. However durability, the chemical mimicking of the process of fibre dissolution using in vitro treatment, is closely related to biopersistence and more readily determined. Here, we describe an experimental process to determine the durability of four types of carbon nanotubes in simulated biological fluid (Gambles solution), and their subsequent pathogenicity in vivo using a mouse model sensitive to inflammogenic effects of fibres. The in vitro and in vivo results were compared with well-characterised glass wool and asbestos fibre controls.

Previous studies have shown no, or very limited, skin penetration of metal oxide nanoparticles following topical application of sunscreens, yet concerns remain about their safety compared to larger particles. Here, we assessed the comparative dermal absorption of a traceable form of Zn ((68)Zn) from (68)ZnO nano-sized and larger particles in sunscreens. Sunscreens were applied to the backs of virgin or pregnant hairless mice over four days. Control groups received topical applications of the sunscreen formulation containing no ZnO particles, or no treatment. Major organs were assessed for changes in (68)Zn/(64)Zn ratios, (68)Zn tracer and total Zn concentrations. Short-term biological impact was assessed by measuring levels of serum amyloid A in blood, and by performing whole-genome transcriptional profiling on livers from each group. Increased concentrations of (68)Zn tracer were detected in internal organs of mice receiving topical applications of (68)ZnO (nano-sized and larger particles), as well as in fetal livers from treated dams, compared with controls. Furthermore, concentrations of (68)Zn in organs of virgin mice treated with sunscreen containing (68)ZnO nanoparticles were found to be significantly higher than in mice treated with sunscreen containing larger (68)ZnO particles. However, no ZnO-mediated change in total Zn concentration in any of the major organs was observed. Thus, despite (68)Zn absorption, which may have been in the form of soluble (68)Zn species or (68)ZnO particles (not known), Zn homeostasis was largely maintained, and the presence of ZnO particles in sunscreen did not elicit an adverse biological response in the mice following short-term topical applications.

Background: Batch effects are a persistent and pervasive form of measurement noise which undermine the scientific utility of high-throughput genomic datasets. At their most benign, they reduce the power of statistical tests resulting in actual effects going unidentified. At their worst, they constitute confounds and render datasets useless. Attempting to remove batch effects will result in some of the biologically meaningful component of the measurement (i.e. signal) being lost. We present and benchmark a novel technique, calledHarman. Harman maximises the removal of batch noise with the constraint that the risk of also losing biologically meaningful component of the measurement is kept to a fraction which is set by the user.Results: Analyses of three independent publically available datasets reveal that Harman removes more batch noise and preserves more signal at the same time, than the current leading technique. Results also show that Harman is able to identify and remove batch effects no matter what their relative size compared to other sources of variation in the dataset. Of particular advantage for meta-analyses and data integration is Harman’s superior consistency in achieving comparable noise suppression - signal preservation trade-offs across multiple datasets, with differing number of treatments, replicates and processing batches.Conclusion: Harman’s ability to better remove batch noise, and better preserve biologically meaningful signal simultaneously within a single study, and maintain the user-set trade-off between batch noise rejection and signal preservation across different studies makes it an effective alternative method to deal with batch effects in high-throughput genomic datasets. Harman is flexible in terms of the data types it can process. It is available publically as an R package (https://bioconductor.org/packages/release/bioc/html/Harman.html), as well as a compiled Matlab package (http://www.bioinformatics.csiro.au/harman/) which does not require a Matlab license to run.