Author/Authors :
Yang, Xiuzhi Tianjin University of Science & Technology - Dagu South Road - Hexi District - Tianjin, China , Wu, Yu Department of Orthopaedic - Tianjin Medical University General Hospital - Anshan Road - Heping District - Tianjin, China , Li, Jiqing Tianjin University of Science & Technology - Dagu South Road - Hexi District - Tianjin, China , Yin, Wuliang School of Electronic and Electrical Engineering - University of Manchester - Manchester, UK , An, Yang Tianjin University of Science & Technology - Dagu South Road - Hexi District - Tianjin, China , Wang, Yanfen Tianjin University of Science & Technology - Dagu South Road - Hexi District - Tianjin, China , Wang, Man Tianjin University of Science & Technology - Dagu South Road - Hexi District - Tianjin, China , Wu, Qiuli Department of Orthopaedic - Tianjin Medical University General Hospital - Anshan Road - Heping District - Tianjin, China , Qu, Zhigang Tianjin University of Science & Technology - Dagu South Road - Hexi District - Tianjin, China , Ning, Guangzhi Department of Orthopaedic - Tianjin Medical University General Hospital - Anshan Road - Heping District - Tianjin, China , Feng, Shiqing Department of Orthopaedic - Tianjin Medical University General Hospital - Anshan Road - Heping District - Tianjin, China
Abstract :
To investigate how a back propagation neural network based on genetic algorithm (GA-BPNN) optimizes the low-intensity pulsed
ultrasound (LIPUS) stimulation parameters to improve the bone marrow mesenchymal stem cells (BMSCs) viability further. 1e
LIPUS parameters were set at various frequencies (0.6, 0.8, 1.0, and 1.2 MHz), voltages (5, 6, 7, and 8 V), and stimulation durations
(3, 6, and 9 minutes). As only some discrete points can be set up in the experiments, the optimal LIPUS stimulation parameter may
not be in the value of these settings. 1e GA-BPNN algorithm is used to optimize parameters of LIPUS to increase the BMSCs
viability further. 1e 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) under the optimized
condition of 6.92 V, 1.02 MHz, and 7.3 min. LIPUS is able to improve the BMSCs viability, which can be improved further by
LIPUS with parameter optimization via GA-BPNN algorithm.
Keywords :
Low-Intensity , Parameter-Optimized , Mesenchymal , GA-BPNN
