Increased mechanical loading through controlled swimming exercise induces bone formation and mineralization in adult zebrafish.

Exercise promotes gain in bone mass through adaptive responses of the vertebrate skeleton. This mechanism counteracts age- and disease-related skeletal degradation, but remains to be fully understood. In life sciences, zebrafish emerged as a vertebrate model that can provide new insights into the complex mechanisms governing bone quality. To test the hypothesis that musculoskeletal exercise induces bone adaptation in adult zebrafish and to characterize bone reorganization, animals were subjected to increased physical exercise for four weeks in a swim tunnel experiment. Cellular, structural and compositional changes of loaded vertebrae were quantified using integrated high-resolution analyses. Exercise triggered rapid bone adaptation with substantial increases in bone-forming osteoblasts, bone volume and mineralization. Clearly, modeling processes in zebrafish bone resemble processes in human bone. This study highlights how exercise experiments in adult zebrafish foster in-depth insight into aging-related bone diseases and can thus catalyze the search for appropriate prevention and new treatment options.

Generation of a probabilistic arterial cerebrovascular atlas derived from 700 time-of-flight MRA datasets.

The cerebral vasculature is a complex vessel network with high variations among human subjects. Although the coarse structure and spatial relationships of the main cerebrovascular branches are well known, not much knowledge about inter-individual vessel variability of humans at a finer level is available. The aim of this work is to present a probabilistic atlas of cerebral arterial vascular structures derived from 700 Time-of-Flight (TOF) magnetic resonance angiography (MRA) datasets of healthy subjects. Therefore, the cerebrovascular system was automatically segmented in each TOF datasets. In a following step, each TOF dataset and corresponding segmentation was registered to the MNI brain atlas. The registered datasets were then used for generation of a probabilistic cerebrovascular atlas. The generated atlas was evaluated with respect to three possible applications. The results suggest that the atlas is especially helpful to obtain knowledge about the cerebrovascular anatomy and its variations in terms of vessel occurrence probability. Furthermore, it appears useful for initialization of automatic cerebrovascular segmentation methods while an application for detection of vessel pathologies seems only feasible for large malformations.