Study On Cell Viability Enhancement Technology Based On Low Initensity Ultrasound Stimulation

Bone marrow mesenchymal stem cells(BMSCs)transplantation is an effective method to treat SCI.Low-intensity pulsed ultrasound(LIPUS)has been reported to be able to enhance the cell viability,which is beneficial for treating spinal cord injury(SCI)through cell transplantation.However,how to achieve the optimal LIPUS stimulation parameters to increase the BMSCs viability further has not been reported yet.In the experiments,BMSCs were assigned to several groups,one for control group and the others for LIPUS groups.The LIPUS parameters were set at various frequencies(0.6 MHz,0.8 MHz,1.0 MHz and 1.2 MHz),voltages(5 V,6 V,7 V and 8 V)and stimulation durations(3 min,6 min and 9 min).Only some discrete points can be set up in the experiments,hence the optimal LIPUS stimulation parameter may not be in the value of these settings.In this study,a back propagation neural network is employed to find the optimal LIPUS stimulation parameters to improve the BMSCs viability further.As an effective neural network learning algorithm,Error Back Propagation(BP)algorithm is widely used in the field of prediction for the ability to deal with nonlinear problems.At the same time,BP neural network which is an effective neural network learning algorithm can deal with the above problem.Through the optimization of genetic algorithm(GA),BP neural network can overcome the shortcomings of slow convergence speed and easy to fall into local extremum,so as to output the ideal optimal parameter combination value.According to the experimental data,the experimental parameters were optimized by the GA-BPNN to improve the viability of BMSCs further.The BMSCs viability of the LIPUS-treated group was improved up to 19.57%(P<0.01).With the optimization via the GA-BPNN algorithm,the viability of BMSCs was further improved by about 5.36%(P<0.01).The experimental data verified that the GA-BPNN algorithm is able to optimize parameters of LIPUS to increase the BMSCs viability further.Furthermore,the validation experiments also show that the neural network is the best combination of parameters consistent with the prediction results.In the experiment,a rat model of SCI was established,and BMSCs transplantation was performed.According to the scores of motor function(Basso-Beattle-Bresnaha,BBB)and histopathological analysis,the spinal cord recovered well in Wistar rats.Therefore,BMSCs transplantation contributes to the repair of SCI.