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Optimization of nanoparticles for cardiovascular tissue engineering

机译：用于心血管组织工程的纳米颗粒的优化

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摘要

Nano-particulate delivery systems have increasingly been playing important roles in cardiovascular tissue engineering. Properties of nanoparticles (e.g. size, polydispersity, loading capacity, zeta potential, morphology) are essential to system functions. Notably, these characteristics are regulated by fabrication variables, but in a complicated manner. This raises a great need to optimize fabrication process variables to ensure the desired nanoparticle characteristics. This paper presents a comprehensive experimental study on this matter, along with a novel method, the so-called Geno-Neural approach, to analyze, predict and optimize fabrication variables for desired nanoparticle characteristics. Specifically, ovalbumin was used as a protein model of growth factors used in cardiovascular tissue regeneration, and six fabrication variables were examined with regard to their influence on the characteristics of nanoparticles made from high molecular weight poly(lactide-co-glycolide). The six-factor five-level central composite rotatable design was applied to the conduction of experiments, and based on the experimental results, a geno-neural model was developed to determine the optimum fabrication conditions. For desired particle sizes of 150, 200, 250 and 300 nm, respectively, the optimum conditions to achieve the low polydispersity index, higher negative zeta potential and higher loading capacity were identified based on the developed geno-neural model and then evaluated experimentally. The experimental results revealed that the polymer and the external aqueous phase concentrations and their interactions with other fabrication variables were the most significant variables to affect the size, polydispersity index, zeta potential, loading capacity and initial burst release of the nanoparticles, while the electron microscopy images of the nanoparticles showed their spherical geometries with no sign of large pores or cracks on their surfaces. The release study revealed that the onset of the third phase of release can be affected by the polymer concentration. Circular dichroism spectroscopy indicated that ovalbumin structural integrity is preserved during the encapsulation process. Findings from this study would greatly contribute to the design of high molecular weight poly(lactide-co-glycolide) nanoparticles for prolonged release patterns in cardiovascular engineering.
机译：纳米颗粒输送系统在心血管组织工程中越来越重要。纳米颗粒的性质（例如尺寸，多分散性，负载能力，ζ电势，形态）对于系统功能至关重要。值得注意的是，这些特征由制造变量来调节，但是以复杂的方式。这就非常需要优化制造工艺变量以确保所需的纳米粒子特性。本文提供了对此问题的综合实验研究，以及一种新颖的方法，即所谓的Geno-Neural方法，可以分析，预测和优化所需纳米粒子特性的制造变量。具体而言，卵白蛋白被用作心血管组织再生中使用的生长因子的蛋白质模型，并检查了六个制造变量对它们对由高分子量聚丙交酯-乙交酯共聚物制成的纳米颗粒特性的影响。将六因素五级中央复合材料可旋转设计应用于实验的进行，并基于实验结果，开发了遗传-神经模型来确定最佳制造条件。对于期望的分别为150、200、250和300 nm的粒径，基于已开发的基因神经模型确定了实现低多分散指数，更高的负zeta电位和更高的负载能力的最佳条件，然后进行了实验评估。实验结果表明，聚合物和外部水相浓度以及它们与其他制造变量的相互作用是影响纳米粒子的大小，多分散指数，ζ电势，负载能力和初始爆裂释放的最重要变量，而电子显微镜观察纳米颗粒的图像显示出其球形几何形状，在其表面没有大的孔或裂纹的迹象。释放研究表明，释放的第三阶段可能会受到聚合物浓度的影响。圆二色性光谱表明在包封过程中卵白蛋白的结构完整性得以保留。这项研究的发现将大大有助于设计用于心血管工程中延长释放模式的高分子量聚（丙交酯-共-乙交酯）纳米颗粒。

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