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A Pilot Study of Parameter-Optimized Low-Intensity Pulsed Ultrasound Stimulation for the Bone Marrow Mesenchymal Stem Cells Viability Improvement

机译:参数优化的低强度脉冲超声刺激改善骨髓间充质干细胞活力的实验研究

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摘要

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. The 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. The GA-BPNN algorithm is used to optimize parameters of LIPUS to increase the BMSCs viability 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) 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.
机译:研究基于遗传算法(GA-BPNN)的反向传播神经网络如何优化低强度脉冲超声(LIPUS)刺激参数,以进一步提高骨髓间充质干细胞(BMSCs)的生存能力。 LIPUS参数设置为各种频率(0.6、0.8、1.0和1.2 MHz),电压(5、6、7和8 V)和刺激持续时间(3、6和9分钟)。由于只能在实验中设置一些离散点,因此最佳LIPUS刺激参数可能不在这些设置的值内。 GA-BPNN算法用于优化LIPUS的参数,以进一步提高BMSCs的生存能力。 LIPUS治疗组的BMSCs生存能力提高了19.57%(P <0.01)。通过GA-BPNN算法进行优化,在6.92 V,1.02 MHz和7.3 min的优化条件下,BMSC的生存能力进一步提高了约5.36%(P <0.01)。 LIPUS能够提高BMSC的生存能力,而LIPUS可以通过GA-BPNN算法对参数进行优化,从而进一步提高其生存能力。

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