关键词: 3D-printed capsule scaffold Artificial neural network Characterization Chlorogenic acid Controlled delivery Fabrication Releasing kinetics

Mesh : Chlorogenic Acid / chemistry Colon Neural Networks, Computer Printing, Three-Dimensional

来  源:   DOI:10.1016/j.foodres.2023.113612

Abstract:
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.
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。本研究旨在制造优化的三维(3D)打印胶囊支架和CGA胶囊,用于将疏水性CGA靶向递送至结肠。使用神经网络模型确定的优化打印参数是170°C的温度,20毫米/秒的印刷速度,喷嘴直径为0.3mm。胶囊表现出CGA的缓释特性,Eudragit®FS30D密封胶囊的释放速率(由于更多的裂缝和空隙)比Eudragit®S100密封胶囊的释放速率更快。Ritger-peppas模型是描述8个CGA胶囊(R2≥0.98)中CGA释放过程的最佳拟合模型。所有CGA胶囊均表现出剪切稀化特性,在低剪切速率下具有稳定的溶胶-凝胶粘度。FTIR光谱证实在CGA和溶胶之间形成非共价键。总的来说,获得的3D打印胶囊为个性化膳食补充剂的开发中CGA的靶向递送提供了有希望的载体。
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