Nanostructure of PEO-polyurethane-PEO triblock copolymer micelles in water.

Novel hydrophilic triblock copolymers which form micelles in aqueous solution were studied by static and dynamic light scattering (SLS and DLS), small angle neutron scattering (SANS) and densitometry. The polymers were symmetric A–B–A block copolymers having two poly(ethylene oxide) (PEO) tail blocks and a polyurethane (PU) center segment that contained pendant carboxylic acids. The aggregation number of the micelles decreased with increasing PEO mass content. When attempting to fit the SANS data it was found that no single model was suitable over the entire range of block lengths and PEO mass concentrations investigated here. For the polymer with the highest aggregation number, the data were fitted with a triblock model consisting of a homogeneous core with a corona of non-interacting Gaussian chains for which only two free parameters were required: the radius of the core and the radius of gyration of the corona. In this case, the core was found to be effectively dry. At lower aggregation numbers, a star polymer model generated significantly better fits, suggesting the absence of any identifiable central core structure. Good agreement was found between the sizes measured by DLS, SANS and theoretical predictions of micelle size from a density distribution theory. These results show that when significant changes in aggregation number occur, the nanostructure of the micelle can change substantially even for polymers that are remarkably similar. © 2010, Elsevier Ltd

Mapping the human genetic architecture of COVID-19

The genetic make-up of an individual contributes to the susceptibility and response to viral infection. Although environmental, clinical and social factors have a role in the chance of exposure to SARS-CoV-2 and the severity of COVID-191,2, host genetics may also be important. Identifying host-specific genetic factors may reveal biological mechanisms of therapeutic relevance and clarify causal relationships of modifiable environmental risk factors for SARS-CoV-2 infection and outcomes. We formed a global network of researchers to investigate the role of human genetics in SARS-CoV-2 infection and COVID-19 severity. Here we describe the results of three genome-wide association meta-analyses that consist of up to 49,562 patients with COVID-19 from 46 studies across 19 countries. We report 13 genome-wide significant loci that are associated with SARS-CoV-2 infection or severe manifestations of COVID-19. Several of these loci correspond to previously documented associations to lung or autoimmune and inflammatory diseases3,4,5,6,7. They also represent potentially actionable mechanisms in response to infection. Mendelian randomization analyses support a causal role for smoking and body-mass index for severe COVID-19 although not for type II diabetes. The identification of novel host genetic factors associated with COVID-19 was made possible by the community of human genetics researchers coming together to prioritize the sharing of data, results, resources and analytical frameworks. This working model of international collaboration underscores what is possible for future genetic discoveries in emerging pandemics, or indeed for any complex human disease