Biotechnology Center, National Chung Hsing University, 250 Kuo-kuang Road, Taichung 40227, Taiwan.
Department of Seafood Science, National Kaohsiung Marine University, 142 Haijhuan Road, Nanzih District, Kaohsiung 81143, Taiwan.
Ultrason Sonochem. 2017 May;36:112-122. doi: 10.1016/j.ultsonch.2016.11.016. Epub 2016 Nov 14.
Piceid, a naturally occurring derivative of resveratrol found in many plants, has recently been considered as a potential nutraceutical. However, its poorly water-soluble property could cause a coupled problem of biological activities concerning drug dispersion and absorption in human body, which is still unsolved now. Liposome, a well-known aqueous carrier for water-insoluble ingredients, is commonly applied in drug delivery systems. In this study, a feasible approach for solving the problem is that the targeted piceid was encapsulated into a liposomal formula as aqueous substrate to overcome its poor water-solubility. The encapsulation process was assisted by ultrasound, with investigation of lipid content, ultrasound power and ultrasound time, for controlling encapsulation efficiency (E.E%), absolute loading (A.L%) and particle size (PS). Moreover, both RSM and ANN methodologies were further applied to optimize the ultrasound-assisted encapsulation process. The data indicated that the most important effects on the encapsulation performance were found to be of lipid content followed by ultrasound time and ultrasound power. The maximum E.E% (75.82%) and A.L% (2.37%) were exhibited by ultrasound assistance with the parameters of 160mg lipid content, ultrasound time for 24min and ultrasound power of 90W. By methodological aspects of processing, the predicted E.E% and A.L% were respectively in good agreement with the experimental results for both RSM and ANN. Moreover, RMSE, R and AAD statistics were further used to compare the prediction abilities of RSM and ANN based on the validation data set. The results indicated that the prediction accuracy of ANN was better than that of RSM. In conclusion, ultrasound-assisted liposome encapsulation can be an efficient strategy for producing well-soluble/dispersed piceid, which could be further applied to promote human health by increased efficiency of biological absorption, and the process of ultrasound-mediated liposome encapsulation can be well established by a methodological approach using either RSM or ANN, but it is worth mentioning that the ANN model used here showed the superiority over RSM for predicting and optimizing encapsulation.
白皮杉醇是一种天然存在的白藜芦醇衍生物，存在于许多植物中，最近被认为是一种有潜力的营养保健品。然而，其较差的水溶性可能会导致生物活性方面的问题，即药物在人体内的分散和吸收，这一问题目前尚未得到解决。脂质体是一种常用于水不溶性成分的水性载体，常用于药物传递系统。在本研究中，一种可行的方法是将靶向白皮杉醇包封到脂质体配方中作为水性基质，以克服其较差的水溶性。该包封过程由超声辅助，考察了脂质含量、超声功率和超声时间对包封效率（E.E%）、绝对载药量（A.L%）和粒径（PS）的影响。此外，还进一步应用 RSM 和 ANN 方法优化了超声辅助包封过程。结果表明，对包封性能最重要的影响因素是脂质含量，其次是超声时间和超声功率。在 160mg 脂质含量、超声时间 24min 和超声功率 90W 的条件下，超声辅助作用下的最大 E.E%（75.82%）和 A.L%（2.37%）。从方法学方面来看，RSM 和 ANN 的预测 E.E%和 A.L%与实验结果分别具有良好的一致性。此外，还进一步使用 RMSE、R 和 AAD 统计数据来比较基于验证数据集的 RSM 和 ANN 的预测能力。结果表明，ANN 的预测精度优于 RSM。综上所述，超声辅助脂质体包封可以作为一种有效的策略来生产水溶性/分散性良好的白皮杉醇，这可以通过提高生物吸收效率来进一步促进人类健康，并且可以通过使用 RSM 或 ANN 的方法学方法来很好地建立超声介导的脂质体包封过程，但值得注意的是，本文使用的 ANN 模型在预测和优化包封方面优于 RSM。
