Animal models are an important part of studying, understanding and designing therapies against neurologic disorders. With the help of’s deep learning based segmentation technology Zhu Peng-Peng and his co-authors could establish and characterize a mouse model to study hereditary spastic paraplegias (HSPs). The model features morphology changes of the endoplasmic reticulum (ER) which appears in a ladder like phenotype, as well as changes in mitochondrial morphology and cytoskeletal organization. These characterizations have been performed using volume electron microscopy and segmentation of the 3d data with our 3dEMTrace pipeline.

Congratulations to all authors!