https://www.selleckchem.com/Bcl-2.html Gait exercise assist robot (GEAR), a gait rehabilitation robot developed for poststroke gait disorder, has been shown to improve walking speed and to improve the poststroke gait pattern. However, the persistence of its beneficial effect has not been clarified. In this matched case-control study, we assessed the durability of the effectiveness of GEAR training in patients with subacute stroke on the basis of clinical evaluation and three-dimensional (3D) gait analysis. Gait data of 10 patients who underwent GEAR intervention program and 10 patients matched for age, height, ***, affected side, type of stroke, and initial gait ability who underwent conventional therapy were extracted from database. The outcome measures were walk score of Functional Independence Measure (FIM-walk), Stroke Impairment Assessment Set total lower limb motor function score (SIAS-L/E), and 3D gait analysis data (spatiotemporal factors and abnormal gait patter indices) at three time points baseline, at the end of intervention, and w of GEAR training in a larger sample. The results indicated significant improvement in the GEAR group after the training period, with respect to both clinical parameters and the gait pattern indices. This improvement was not evident in the control group after the training period. The results possibly support the effectiveness of GEAR training in conferring persistently efficient gait patterns in patients with poststroke gait disorder. Further studies should investigate the long-term effects of GEAR training in a larger sample.The growing importance of astrocytes in the field of neuroscience has led to a greater number of computational models devoted to the study of astrocytic functions and their metabolic interactions with neurons. The modeling of these interactions demands a combined understanding of brain physiology and the development of computational frameworks based on genomic-scale reconstructions, system biology, and dyn