The role of networks to overcome large-scale challenges in tomography : the non-clinical tomography users research network

Our ability to visualize and quantify the internal structures of objects via computed tomography (CT) has fundamentally transformed science. As tomographic tools have become more broadly accessible, researchers across diverse disciplines have embraced the ability to investigate the 3D structure-function relationships of an enormous array of items. Whether studying organismal biology, animal models for human health, iterative manufacturing techniques, experimental medical devices, engineering structures, geological and planetary samples, prehistoric artifacts, or fossilized organisms, computed tomography has led to extensive methodological and basic sciences advances and is now a core element in science, technology, engineering, and mathematics (STEM) research and outreach toolkits. Tomorrow's scientific progress is built upon today's innovations. In our data-rich world, this requires access not only to publications but also to supporting data. Reliance on proprietary technologies, combined with the varied objectives of diverse research groups, has resulted in a fragmented tomography-imaging landscape, one that is functional at the individual lab level yet lacks the standardization needed to support efficient and equitable exchange and reuse of data. Developing standards and pipelines for the creation of new and future data, which can also be applied to existing datasets is a challenge that becomes increasingly difficult as the amount and diversity of legacy data grows. Global networks of CT users have proved an effective approach to addressing this kind of multifaceted challenge across a range of fields. Here we describe ongoing efforts to address barriers to recently proposed FAIR (Findability, Accessibility, Interoperability, Reuse) and open science principles by assembling interested parties from research and education communities, industry, publishers, and data repositories to approach these issues jointly in a focused, efficient, and practical way. By outlining the benefits of networks, generally, and drawing on examples from efforts by the Non-Clinical Tomography Users Research Network (NoCTURN), specifically, we illustrate how standardization of data and metadata for reuse can foster interdisciplinary collaborations and create new opportunities for future-looking, large-scale data initiatives

Vertebral morphology in the tail-whipping common thresher shark, Alopias vulpinus

Thresher sharks (Alopias spp.) are characterized by an elongated, scythe-like caudal fin that is used in tail-whipping, a behaviour where the tail is thrown overhead to stun prey. Tail-whipping is performed via extreme dorsoventral bending of the vertebral column, and is dramatically different from lateral oscillatory motion used for swimming. Previous work has examined thresher shark vertebral morphology and mechanical properties, but in the context of swimming loads. Our goal was to assess centra morphometrics and microarchitecture for variations that may support extreme dorsoventral bending. We examined anterior and posterior body vertebrae from an embryo, five juvenile, and four adult thresher sharks using micro-computed tomography. We used principal component and landmark analyses to examine variables influencing vertebral morphology and mineral arrangement, respectively. We found that morphology and microstructure significantly varied across body regions and ontogeny. We hypothesize that anterior body vertebrae increase stability, while posterior body vertebrae support the caudal fin. Vertebral size and quantity of mineral structures (lamellae and nodes) increased across ontogeny, suggesting vertebrae adapt over development to support a larger body and tail. Based on our results, we hypothesize that thresher shark vertebrae vary in morphometrics and mineralization (amount and arrangement) supporting the mechanical needs for tail-whipping