We first introduce the concept of statistically defined nanoscale geometries that go beyond the current practice of borrowing “family” names from common objects (“nanoflowers”’ “nanostars”, “urchin-like”, etc.) 43, 44, 45, 46. We will use that discussion to raise the question of “biological shape identity”. While many disciplines will value a quantitative framework for nanoscale shape, here we discuss the two interwoven arenas of nanoscale shape statistics, nanoparticle synthetic control (framed by quantitative measures of shape), and the resulting linkage of those well-controlled shape ensembles to cellular read-outs. Thereby, arenas extending from the science of immunological adjuvants to the biological and clinical impacts of environmental dusts (currently phenomenological in approach, lacking any substantive quantitative basis for development) may be advanced. Such a quantitative framework with the capacity to describe the relevant aspects of shape ensembles might also link nanoparticle shape statistics to biological function in new and hitherto undiscovered ways. These general limitations become very significant barriers to understanding the link between nanoscale shape ensembles and biology, and progress there now requires new ways of thinking, new concepts, as well as practical innovations.Īs a basic step we require a quantitative statistical definition of nanoscale shape that can ensure complex shape ensembles are meaningfully reproduced and their properties communicated. We currently find ourselves unable to even name and share information, let alone carry out many systematic investigations of them. Also, advancing synthetic methods now potentially offer “unlimited” freedom to controllably make a new universe of such complex geometrical ensembles that cannot be described, recognized or characterized with only a few length parameters 36, 37, 38, 39, 40, 41, 42. However, everywhere in our surroundings we increasingly make (purposefully or by accident, as in 3D printing) nanoscale shape ensembles, that possess complex features on length-scales comparable to the particle itself 29, 30, 31, 32, 33, 34, 35. Various aspects of shape at different length scales have always been implicitly involved in nanoscience 14, 15, 16, 17, 18, 19, 20 nanostructures are never smooth and spherical (on an atomic or few-atom scale) by virtue of their synthetic or other origin, and also some highly non-spherical (for example rod-like) objects are quite well studied 21, 22, 23, 24, 25, 26, 27, 28. The idea that “biology sees nanoscale shape” and that certain shape features could also specifically regulate (or even target) given biological pathways is an intriguing but still emerging concept 7, 8, 9, 10, 11, 12, 13. It is now clear that man-made nanoscale objects are processed by the whole range of endogenous biological machinery, in part via their in situ biomolecular corona surface 1, 2, 3, 4, 5, 6. We show how these ideas may be applied to the interaction between the nanoscale-shape and the living universe and provide a conceptual framework for the study of nanoscale shape biological recognition and identity. We find the natural emergence of intrinsic shape groups as well-defined ensemble distributions and show how these may be analyzed and interpreted to reveal novel aspects of our nanoscale shape environment. Here we capture and digitise particle shape information on the relevant size scale and create a condensed representation in which the essential shape features can be captured, recognized and correlated. With the ever growing universe of nanoscale shapes, names such as “nanoflowers” and “nanostars” no longer precisely describe or characterise the distinct nature of the particles. Such shape ensembles can be made by modern nano-synthetic methods and many industrial processes. Everywhere in our surroundings we increasingly come in contact with nanostructures that have distinctive complex shape features on a scale comparable to the particle itself.
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