Background: Recent advances in tissue clearing techniques, combined with high-speed image acquisition through light sheet microscopy, enable rapid three-dimensional (3D) imaging of biological specimens, such as whole mouse brains, in a matter of hours. Quantitative analysis of such 3D images can help us understand how changes in brain structure lead to differences in behavior or cognition, but distinguishing densely packed features of interest, such as nuclei, from background can be challenging. Recent deep learning-based nuclear segmentation algorithms show great promise for automated segmentation, but require large numbers of accurate manually labeled nuclei as training data.
View Article and Find Full Text PDFPurpose: Patient presentation after brachial plexus birth injury (BPBI) is influenced by nerve injury location; more contracture and bone deformity occur at the shoulder in postganglionic injuries. Although bone deformity after postganglionic injury is well-characterized, the extent of glenohumeral deformity after preganglionic BPBI is unclear.
Methods: Twenty Sprague-Dawley rat pups received preganglionic or postganglionic neurectomy on a single forelimb at postnatal days 3 to 4.