Effect of Motor Imagery Training with Sensory Feedback on Sensory-Motor Function of the Upper Extremity in Patients with Chronic Stroke

BACKGROUND AND OBJECTIVE: Conventional rehabilitation in stroke patients is more likely to use repetitive movements to improve motor function, which may be difficult for people with motor limitations. Mental imagery training can be done without moving the affected limbs, and this method is safe, cheap and accessible. The aim of this study is to investigate the effect of motor imagery training with sensory feedback on sensory-motor function of the upper extremity in patients with chronic stroke. METHODS: In this non-randomized clinical trial, 30 stroke patients with level of upper extremity function according to Brunnsrom’s recovery ≥ 2, and cognitive function level according to MMSE ≥ 21 were selected through non-probability sampling from rehabilitation centers and randomly divided into intervention and control groups. Patients in the control group received conventional rehabilitation programs, and patients in the intervention group received motor imagery training with sensory feedback in 12 sessions (45 – 60 minutes), in addition to conventional rehabilitation programs. Before and after the interventions, sensory and motor functions were assessed using Box-Block test, Purde-Pegbord test, range of motion, FMA-UE total and FMA-UE coordination/speed, 2-point-discrimination, Nottingham-Sensory Assessment, Modified-Ashworth Scale and Stroke Impact Scale. FINDINGS: Mean percentage of changes in motor function and speed/coordination of upper extremity, shoulder and elbow range of motion and gross dexterity was higher in the interventional group (50%, 50%, 80%, 50% and 80%, respectively) compared with the conventional rehabilitation group (20%, 18%, 50%, 30% and 30%, respectively) (p≤0.05). However, both interventions had similar effect on sensory function, fine dexterity, muscle tone and activities of daily living. CONCLUSION: The results of the study showed that motor imagery training with sensory feedback along with conventional rehabilitation could enhance the motor function, gross dexterity and range of motion of the upper extremity in chronic stroke patients

Epitope Prediction by Novel Immunoinformatics Approach: A State-of-the-art Review

Immunoinformatics is a science that helps to create significant immunological information using bioinformatics softwares and applications. One of the most important applications of immunoinformatics is the prediction of a variety of specific epitopes for B cell recognition and T cell through MHC class I and II molecules. This method reduces costs and time compared to laboratory tests. In this state-of-the-art review, we review about 50 papers to find the latest and most used immunoinformatic tools as well as their applications for predicting the viral, bacterial and tumoral structural and linear epitopes of B and T cells. In the clinic, the main application of prediction of epitopes is for designing peptide-based vaccines. Peptide-based vaccines are a considerably potential alternative to low-cost vaccines that may reduce the risks related to the production of common vaccines. © 2019, Springer Nature B.V