Structural colours in living organisms have been observed and analysed in a large number of species, however the study of how the micro- and nano-scopic natural structures responsible of such colourations develop has been largely ignored. Understanding the interplay between chemical composition, structural morphology on multiple length scales, and mechanical constraints requires a range of investigation tools able to capture the different aspects of natural hierarchical architectures. Here, we report a developmental study of the most widespread strategy for structural colouration in nature: the cuticular multilayer. In particular, we focus on the exoskeletal growth of the dock leaf beetle Gastrophysa viridula, capturing all aspects of its formation: the macroscopic growth is tracked via synchrotron microtomography, while the submicron features are revealed by electron microscopy and light spectroscopy combined with numerical modelling. In particular, we observe that the two main factors driving the formation of the colour-producing multilayers are the polymerization of melanin during the ecdysis and the change in the layer spacing during the sclerotisation of the cuticle. Our understanding of the exoskeleton formation provides a unique insight into the different processes involved during metamorphosis.
α1-Antitrypsin (α1-AT) deficiency may play a role in arterial aneurysmal disease by allowing increased proteolysis of arterial structural proteins. α1-AT levels are influenced by variation at the PI (protease inhibitor) locus. PI phenotypes were determined in 173 patients with abdominal aortic aneurysms (77 from Pitsburgh, 96 from London) and in 72 patients with intracranial aneurysms (26 from Pittsburgh, 46 from London). No excess of PI deficiency alleles was observed in either of the aortic aneurysm data sets or in the Pittsburgh intracranial aneurysm data. The PPZ deficiency allele frequency in the London intracranial aneurysm data was 8-fold higher than in controls; however, this was not significant after correcting for multiple comparisons. PI phenotype had no effect on aneurysm age-at-diagnosis within any of the data sets. Smoking history had an effect on aneurysm age-at-diagnosis only within the Pittsburgh intracranial-aneurysm data.
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