Palukuru Uday P, Hanifi Arash, McGoverin Cushla M, Devlin Sean, Lelkes Peter I, Pleshko Nancy
Department of Bioengineering, Temple University, 1947 N. 12th St, Philadelphia, PA, USA.
Department of Bioengineering, Temple University, 1947 N. 12th St, Philadelphia, PA, USA.
Anal Chim Acta. 2016 Jul 5;926:79-87. doi: 10.1016/j.aca.2016.04.031. Epub 2016 Apr 25.
Disease or injury to articular cartilage results in loss of extracellular matrix components which can lead to the development of osteoarthritis (OA). To better understand the process of disease development, there is a need for evaluation of changes in cartilage composition without the requirement of extensive sample preparation. Near infrared (NIR) spectroscopy is a chemical investigative technique based on molecular vibrations that is increasingly used as an assessment tool for studying cartilage composition. However, the assignment of specific molecular vibrations to absorbance bands in the NIR spectrum of cartilage, which arise from overtones and combinations of primary absorbances in the mid infrared (MIR) spectral region, has been challenging. In contrast, MIR spectroscopic assessment of cartilage is well-established, with many studies validating the assignment of specific bands present in MIR spectra to specific molecular vibrations. In the current study, NIR imaging spectroscopic data were obtained for compositional analysis of tissues that served as an in vitro model of OA. MIR spectroscopic data obtained from the identical tissue regions were used as the gold-standard for collagen and proteoglycan (PG) content. MIR spectroscopy in transmittance mode typically requires a much shorter pathlength through the sample (≤10 microns thick) compared to NIR spectroscopy (millimeters). Thus, this study first addressed the linearity of small absorbance bands in the MIR region with increasing tissue thickness, suitable for obtaining a signal in both the MIR and NIR regions. It was found that the linearity of specific, small MIR absorbance bands attributable to the collagen and PG components of cartilage (at 1336 and 856 cm(-1), respectively) are maintained through a thickness of 60 μm, which was also suitable for NIR data collection. MIR and NIR spectral data were then collected from 60 μm thick samples of cartilage degraded with chondroitinase ABC as a model of OA. Partial least squares (PLS) regression using NIR spectra as input predicted the MIR-determined compositional parameters of PG/collagen within 6% of actual values. These results indicate that NIR spectral data can be used to assess molecular changes that occur with cartilage degradation, and further, the data provide a foundation for future clinical studies where NIR fiber optic probes can be used to assess the progression of cartilage degradation.
关节软骨的疾病或损伤会导致细胞外基质成分的丧失，进而可能引发骨关节炎（OA）。为了更好地理解疾病发展过程，需要在无需大量样品制备的情况下评估软骨成分的变化。近红外（NIR）光谱是一种基于分子振动的化学研究技术，越来越多地被用作研究软骨成分的评估工具。然而，将特定分子振动与软骨近红外光谱中的吸收带对应起来具有挑战性，这些吸收带源于中红外（MIR）光谱区域中主要吸收峰的倍频和组合。相比之下，MIR光谱对软骨的评估已经成熟，许多研究验证了MIR光谱中特定谱带与特定分子振动的对应关系。在本研究中，获取了近红外成像光谱数据用于作为OA体外模型的组织的成分分析。从相同组织区域获得的MIR光谱数据被用作胶原蛋白和蛋白聚糖（PG）含量的金标准。与近红外光谱（毫米级）相比，透射模式下的MIR光谱通常需要穿过样品的光程短得多（≤10微米厚）。因此，本研究首先探讨了MIR区域中小吸收带随组织厚度增加的线性关系，这对于在MIR和NIR区域都获得信号是合适的。结果发现，归因于软骨胶原蛋白和PG成分的特定小MIR吸收带（分别在133 cm(-1)和856 cm(-1)）在60μm厚度内保持线性，这对于NIR数据采集也是合适的。然后从用软骨素酶ABC降解的60μm厚软骨样品中收集MIR和NIR光谱数据，作为OA模型。以近红外光谱作为输入的偏最小二乘（PLS）回归预测了MIR测定的PG/胶原蛋白成分参数，预测值与实际值的偏差在6%以内。这些结果表明，近红外光谱数据可用于评估软骨降解过程中发生的分子变化，此外，这些数据为未来临床研究提供了基础，在临床研究中近红外光纤探头可用于评估软骨降解的进展。
