利用人工神经网络优化的3d打印胶囊支架,用于将绿原酸靶向递送到结肠。

Yingsa Wang, Hongzhu Chen, Qiannan Liu, Ruixuan Zhao, Wei Liu, Shucheng Liu, Liang Zhang, Honghai Hu
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引用次数: 0

摘要

绿原酸(CGA)是一种重要的生物活性多酚,具有广泛的生物学特性。本研究旨在制备一种优化的三维(3D)打印胶囊支架和CGA胶囊,用于将疏水CGA靶向递送到结肠。利用神经网络模型确定的优化打印参数为:打印温度170℃,打印速度20 mm/s,喷嘴直径0.3 mm。胶囊具有CGA缓释特性,Eudragit®FS 30d密封胶囊的释放速度(由于更多的裂缝和空隙)比Eudragit®s100密封胶囊更快。Ritger-peppas模型最适合描述8粒CGA胶囊中CGA的释放过程(R2≥0.98)。所有CGA胶囊在低剪切速率下具有稳定的溶胶-凝胶粘度,具有剪切减薄性能。FTIR光谱证实了CGA与溶胶之间形成了非共价键。总体而言,所获得的3d打印胶囊为个性化膳食补充剂开发中的CGA靶向递送提供了一个有希望的载体。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
An optimized 3D-printed capsule scaffold utilizing artificial neural network for the targeted delivery of chlorogenic acid to the colon.

Chlorogenic acid (CGA) is an important bioactive polyphenol with extensive biological properties. This study aimed to fabricate an optimized three-dimensional (3D)-printed capsule scaffold and CGA capsules for targeted delivery of hydrophobic CGA to the colon. The optimized printing parameters identified using the neural network model were a temperature of 170 °C, a printing speed of 20 mm/s, and a nozzle diameter of 0.3 mm. The capsules exhibited slow releasing properties of CGA, and the releasing rates of Eudragit®FS 30D-sealed capsules (due to more cracks and voids) were faster than those of Eudragit®S100-sealed capsules. The Ritger-peppas model was the best fitting model to describe the releasing process of CGA from 8 CGA capsules (R2 ≥ 0.98). All CGA capsules exhibited shear-thinning properties with stable sol-gel viscosity at low shear rates. FTIR spectra confirmed the formation of non-covalent bonds between CGA and the sol. Overall, the obtained 3D-printed capsules provided a promising carrier for the targeted delivery of CGA in the development of personalized dietary supplements.

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