首页> 美国卫生研究院文献>Tissue Engineering. Part A >Near-Infrared Spectroscopy Predicts Compositional and Mechanical Properties of Hyaluronic Acid-Based Engineered Cartilage Constructs
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Near-Infrared Spectroscopy Predicts Compositional and Mechanical Properties of Hyaluronic Acid-Based Engineered Cartilage Constructs

机译:近红外光谱可预测基于透明质酸的工程软骨构建体的组成和力学性能

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摘要

Hyaluronic acid (HA) has been widely used for cartilage tissue engineering applications. However, the optimal time point to harvest HA-based engineered constructs for cartilage repair is still under investigation. In this study, we investigated the ability of a nondestructive modality, near-infrared spectroscopic (NIR) analysis, to predict compositional and mechanical properties of HA-based engineered cartilage constructs. NIR spectral data were collected from control, unseeded constructs, and twice per week by fiber optic from constructs seeded with chondrocytes during their development over an 8-week period. Constructs were harvested at 2, 4, 6, and 8 weeks, collagen and sulfated glycosaminoglycan content measured using biochemical assays, and the mechanical properties of the constructs evaluated using unconfined compression tests. NIR absorbances associated with the scaffold material, water, and engineered cartilage matrix, were identified. The NIR-determined matrix absorbance plateaued after 4 weeks of culture, which was in agreement with the biochemical assay results. Similarly, the mechanical properties of the constructs also plateaued at 4 weeks. A multivariate partial least square model based on NIR spectral input was developed to predict the moduli of the constructs, which resulted in a prediction error of 10% and R value of 0.88 for predicted versus actual values of dynamic modulus. Furthermore, the maximum increase in moduli was calculated from the first derivative of the curve fit of NIR-predicted and actual moduli values over time, and both occurred at ∼2 weeks. Collectively, these data suggest that NIR spectral data analysis could be an alternative to destructive biochemical and mechanical methods for evaluation of HA-based engineered cartilage construct properties.
机译:透明质酸(HA)已广泛用于软骨组织工程应用。但是,仍在研究收获基于HA的工程构建物进行软骨修复的最佳时间点。在这项研究中,我们调查了非破坏性模式,近红外光谱(NIR)分析的能力,以预测基于HA的工程软骨构建体的组成和力学性能。从对照,非播种构建体收集NIR光谱数据,并在8周的发育过程中通过光纤每周两次从播种有软骨细胞的构建体中收集NIR光谱数据。在第2、4、6和8周收获构建体,使用生化测定法测量胶原蛋白和硫酸化的糖胺聚糖含量,并使用无侧限压缩测试评估构建体的机械性能。确定了与支架材料,水和工程软骨基质相关的NIR吸光度。 NIR测定的基质吸光度在培养4周后达到稳定水平,这与生化测定结果一致。类似地,构建体的机械性能在第4周也稳定。开发了基于NIR光谱输入的多元偏最小二乘模型,以预测结构的模量,这导致动态模量的预测值与实际值的预测误差为10%,R值为0.88。此外,模量的最大增加是根据NIR预测的曲线拟合值和实际模量值随时间的一阶导数计算的,并且都在约2周内发生。总的来说,这些数据表明,NIR光谱数据分析可以替代破坏性的生化和机械方法,用于评估基于HA的工程软骨构建体的特性。

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