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Non-destructive Assessment of Engineered Cartilage Composition by Near Infrared Spectroscopy

机译:近红外光谱技术对工程软骨成分的无损评估

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摘要

Tissue engineering presents a strategy to overcome the limitations of current tissue healing methods. Scaffolds, cells, external growth factors and mechanical input are combined in an effort to obtain constructs with properties that mimic native tissues. However, engineered constructs developed using similar culture environments can have very different matrix composition and biomechanical properties. Accordingly, a non-destructive technique to assess constructs during development such that appropriate compositional endpoints can be defined is desirable. Near infrared spectroscopy (NIRS) analysis is a modality being investigated to address the challenges associated with current evaluation techniques, which includes non-destructive compositional assessment. In the present study, cartilage tissue constructs were grown using chondrocytes seeded onto polyglycolic acid (PGA) scaffolds in similar environments in three separate tissue culture experiments and monitored using NIRS. Multivariate partial least squares (PLS) analysis models of NIR spectra were calculated and used to predict tissue composition, with biochemical assay information used as the reference data. Results showed that for combined data from all tissue culture experiments, PLS models were able to assess composition with significant correlations to reference values, including engineered cartilage water (at 5200 cm−1, R = 0.68, p = 0.03), proteoglycan (at 4310 cm−1, R = 0.82, p = 0.007), and collagen (at 4610 cm−1, R = 0.84, p = 0.005). In addition, degradation of PGA was monitored using specific NIRS frequencies. These results demonstrate that NIR spectroscopy combined with multivariate analysis provides a non-destructive modality to assess engineered cartilage, which could provide information to determine the optimal time for tissue harvest for clinical applications.
机译:组织工程学提出了一种克服当前组织愈合方法的局限性的策略。将支架,细胞,外部生长因子和机械输入相结合,以期获得具有模拟天然组织特性的构建体。但是,使用相似的培养环境开发的工程构建体可能具有截然不同的基质组成和生物力学特性。因此,需要一种在开发过程中评估构建体的无损技术,以便可以定义适当的组成终点。近红外光谱(NIRS)分析是一种正在研究以应对与当前评估技术相关的挑战的方法,其中包括无损成分评估。在本研究中,在三个单独的组织培养实验中,在相似的环境中,使用接种到聚乙醇酸(PGA)支架上的软骨细胞培养软骨组织构建体,并使用NIRS对其进行监测。计算了近红外光谱的多元偏最小二乘(PLS)分析模型,并将其用于预测组织组成,并将生化测定信息用作参考数据。结果表明,对于来自所有组织培养实验的组合数据,PLS模型能够评估与参考值具有显着相关性的成分,包括工程软骨水(5200 cm -1 ,R = 0.68,p = 0.03),蛋白聚糖(在4310 cm -1 时,R = 0.82,p = 0.007)和胶原蛋白(在4610 cm -1 时,R = 0.84,p = 0.005) )。此外,使用特定的NIRS频率监控PGA的降解。这些结果表明,近红外光谱结合多变量分析提供了一种非破坏性的方法来评估工程软骨,这可以提供信息来确定临床应用中组织收获的最佳时间。

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