A recent study conducted by researchers from the University of Cologne and Forschungszentrum Jülich has revealed that despite their vastly different body structures, flies, mice, and humans all share a similar walking pattern. Published in the Proceedings of the National Academy of Sciences, the study titled "Cross-species identification of conserved and divergent locomotor kinematic strategies using AutoGaitA" found that all three species display a consistent pattern of joint velocities. In this pattern, joints that are farther from the body's center move faster than those closer to it. This so-called distal-to-proximal velocity gradient remained stable even when the animals walked under different conditions, such as on varied surfaces or at different speeds. To reach this conclusion, the researchers analyzed movement data from various joints in fruit flies, mice, and humans. While each species uses different biological mechanisms to propel itself forward, they all showed a similar pattern in how their joints moved. The study was led by Professors Silvia Daun and Graziana Gatto. To facilitate this cross-species comparison, the researchers created an open-source software called AutoGaitA. This tool allows scientists to analyze movement patterns across different animals using standardized methods, enabling comparisons under various experimental conditions. The study also looked at how aging affects movement in these species. It found that all three experienced a decline in the strength used to push themselves forward, but the specific changes varied due to their anatomical differences. In older humans, the propulsion from the ankle joint was notably reduced. In mice, changes were more pronounced in the knee and ankle joints. Fruit flies showed altered coordination in the flexion of their legs. Despite these species-specific differences, the fundamental ratio of joint velocities remained consistent across all three. This research highlights a shared fundamental principle of motor control that exists even among species that are evolutionarily distant from each other. The open-source software AutoGaitA has potential applications beyond walking, such as studying other rhythmic movements like swimming, flying, or jumping. Scientists believe this framework could be instrumental in researching aging processes and neurological disorders, and it may also help in developing and evaluating rehabilitation techniques.