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Chemical imaging of articular cartilage sections with Raman mapping, employing uni- and multi-variate methods for data analysis

机译：使用单变量和多变量方法进行拉曼映射的关节软骨切片化学成像

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摘要

Raman mapping in combination with uni- and multi-variate methods of data analysis is applied tonarticular cartilage samples. Main differences in biochemical composition and collagen fibersnorientation between superficial, middle and deep zone of the tissue are readily observed in the samples.nCollagen, non-collagenous proteins, proteoglycans and nucleic acids can be distinguished on the basisnof their different spectral characteristics, and their relative abundance can be mapped in the label-freentissue samples, at so high a resolution as to permit the analysis at the level of single cells. Differencesnbetween territorial and inter-territorial matrix, as well as inhomogeneities in the inter-territorial matrix,nare properly identified. Multivariate methods of data analysis prove to be complementary to thenunivariate approach. In particular, our partial least squares regression model gives a semiquantitativenmapping of the biochemical constituents in agreement with average composition found in the literature.nThe combination of hierarchical and fuzzy cluster analysis succeeds in detecting variations betweenndifferent regions of the extra-cellular matrix. Because of its characteristics as an imaging technique,nRaman mapping could be a promising tool for studying biochemical changes in cartilage occurringnduring aging or osteoarthritis.
机译：拉曼映射与单变量和多变量数据分析方法相结合，适用于关节软骨样品。样本中很容易观察到组织的浅层，中层和深层之间生化成分和胶原纤维取向的主要差异.n，胶原，非胶原蛋白，蛋白聚糖和核酸可以根据它们的不同光谱特征及其相对特征进行区分。可以在无标签的组织样本中以足够高的分辨率绘制丰度图，以允许在单细胞水平上进行分析。区域和区域间矩阵之间的差异以及区域间矩阵中的不均匀性都无法正确识别。事实证明，多元数据分析方法是单变量方法的补充。特别是，我们的偏最小二乘回归模型给出了与文献中发现的平均组成一致的生化成分的半定量映射。n层次分析和模糊聚类分析的结合成功地检测了细胞外基质不同区域之间的变化。由于其作为成像技术的特性，nRaman作图可能是研究在衰老或骨关节炎中发生的软骨生化变化的有前途的工具。

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  • 来源
    《The Analyst》 |2010年第12期|p.3193-3204|共12页
  • 作者

    Alois Bonifacio Claudia Beleites Franco Vittur Eleonora Marsich Sabrina Semeraro Sergio Paoletti and Valter Sergo;

  • 作者单位

    aCENMAT Dept. of Materials and Natural Resources, University ofTrieste, Via Valerio 6a, 34100 Trieste, Italy. E-mail: abonifacio@units.it;

    Fax: +39 040 572044;

    Tel: +39 040 558 3768bDept. of Life Sciences, University of Trieste, Via Valerio 6a, 34100Trieste, Italy† This article is part of a themed issue on Optical Diagnosis. This issueincludes work presented at SPEC 2010 Shedding Light on Disease:Optical Diagnosis for the New Millennium, which was held inManchester, UK June 26th–July 1st 2010.‡ Electronic supplementary information (ESI) available: Furtherexperimental results. See DOI: 10.1039/c0an00459f;

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