Studying the interactions between nanoengineered materials and biological systems plays a vital role in the development of biological applications of nanotechnology and the improvement of our fundamental understanding of the bio–nano interface. A significant barrier to progress in this multidisciplinary area is the variability of published literature with regards to characterizations performed and experimental details reported. Here, we suggest a ‘minimum information standard’ for experimental literature investigating bio–nano interactions. This standard consists of specific components to be reported, divided into three categories: material characterization, biological characterization and details of experimental protocols. Our intention is for these proposed standards to improve reproducibility, increase quantitative comparisons of bio–nano materials, and facilitate meta analyses and in silico modelling.

This review describes the challenges, opportunities and recent advances in developing clinically applicable biosensors for integrated body fluid analysis.

This study evaluated three techniques, stimulated emission depletion (STED) microscopy, atomic force microscopy (AFM), and cryogenic scanning electron microscopy (Cryo-SEM), for visualising the morphology and obtaining pore size information of agarose hydrogels (0.38, 1.0, 1.5, 2.0% agarose content). The pore size distributions were obtained using a common manual approach which was validated for Cryo-SEM data using poly(lactic-co-glycolic acid) (PLGA) nanoparticles as an internal standard. There was good agreement in pore size distribution data for agarose hydrogels with an agarose content of 1.0% and higher when using these techniques. For the 1.0% gel sample imaged using STED and Cryo-SEM, no significant difference was observed between these two techniques yielding average pore sizes of 240 and 230 nm, respectively. The average pore size values obtained from AFM images for 1.5 and 2.0% gel samples were significantly smaller by 10–15% compared to values obtained from Cryo-SEM data as predicted due to the AFM tip artefact for concave features. Pros and cons of each technique are discussed in detail.