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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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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 approximate to 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。然而,仍然正在研究收获基于HA的工程构建体的最佳时间点。在这项研究中,我们研究了非破坏性模态,近红外光谱(NIR)分析的能力,预测了HA基工程软骨构建体的组成和机械性能。通过在8周的发展期间,通过从培发的纤维纤维从控制,未对照,未控制的构建体和每周两次收集NIR光谱数据。使用生物化学测定测量的2,4,6和8周,在2,4,6和8周,胶原和硫酸化糖胺聚糖含量,以及使用无凝结的压缩测试评估的构建体的机械性能。鉴定了与支架材料,水和工程化软骨基质相关的鼻炎吸光度。培养4周后,培养4周后的NIR确定的基质吸光度,这与生化测定结果一致。类似地,构建体的机械性能也在4周内达到柔韧。开发了一种基于NIR光谱输入的多变量偏最小二乘模型,以预测构建体的模态,这导致预测误差为10%和R值为0.88的预测与动态模量的实际值。此外,从预测和实际模数值的曲线拟合的第一导数随时间的第一个导数计算模数的最大增加,并且两者近似发生在2周内。总的来说,这些数据表明,NIR光谱数据分析可能是对评估HA基工程软骨构建性能的破坏性生化和机械方法的替代。

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