Department of Chemistry, University of Michigan, Ann Arbor, MI, USA.
Bone. 2012 Apr;50(4):942-53. doi: 10.1016/j.bone.2011.12.026. Epub 2012 Jan 20.
There is growing evidence that bone composition and tissue-level mechanical properties are significant determinants of skeletal integrity. In the current study, Raman spectroscopy and nanoindentation testing were co-localized to analyze tissue-level compositional and mechanical properties in skeletally mature young (4 or 5 months) and old (19 months) murine femora at similar spatial scales. Standard multivariate linear regression analysis revealed age-dependent patterns in the relationships between mechanical and compositional properties at the tissue scale. However, changes in bone material properties with age are often complex and nonlinear, and can be missed with linear regression and correlation-based methods. A retrospective data mining approach was implemented using non-linear multidimensional visualization and classification to identify spectroscopic and nanoindentation metrics that best discriminated bone specimens of different age-classes. The ability to classify the specimens into the correct age group increased by using combinations of Raman and nanoindentation variables (86-96% accuracy) as compared to using individual measures (59-79% accuracy). Metrics that best classified 4 or 5 month and 19 month specimens (2-age classes) were mineral to matrix ratio, crystallinity, modulus and plasticity index. Metrics that best distinguished between 4, 5 and 19 month specimens (3-age classes) were mineral to matrix ratio, crystallinity, modulus, hardness, cross-linking, carbonate to phosphate ratio, creep displacement and creep viscosity. These findings attest to the complexity of mechanisms underlying bone tissue properties and draw attention to the importance of considering non-linear interactions between tissue-level composition and mechanics that may work together to influence material properties with age. The results demonstrate that a few non-linearly combined compositional and mechanical metrics provide better discriminatory information than a single metric or a single technique.
越来越多的证据表明，骨成分和组织水平的力学性能是骨骼完整性的重要决定因素。在本研究中，拉曼光谱和纳米压痕测试被共定位，以在类似的空间尺度上分析骨骼成熟的年轻（4 或 5 个月）和老年（19 个月）小鼠股骨的组织水平组成和力学性能。标准多元线性回归分析显示，在组织水平上，力学性能和组成性能之间的关系存在年龄依赖性模式。然而，随着年龄的增长，骨材料性能的变化往往是复杂和非线性的，并且可能会被线性回归和相关方法所忽略。使用非线性多维可视化和分类来实现回顾性数据挖掘方法，以识别最佳区分不同年龄组骨标本的光谱学和纳米压痕指标。与使用单个指标（59-79%的准确性）相比，使用拉曼和纳米压痕变量的组合（86-96%的准确性）来对标本进行正确的年龄分类的能力提高了。最佳分类 4 或 5 个月和 19 个月标本（2 个年龄组）的指标是矿物质与基质比、结晶度、模量和塑性指数。最佳区分 4、5 和 19 个月标本（3 个年龄组）的指标是矿物质与基质比、结晶度、模量、硬度、交联、碳酸盐与磷酸盐比、蠕变位移和蠕变粘度。这些发现证明了骨骼组织特性的潜在机制的复杂性，并提请注意考虑组织水平组成和力学之间的非线性相互作用的重要性，这些相互作用可能共同作用，随着年龄的增长影响材料性能。结果表明，几个非线性组合的组成和力学指标比单个指标或单一技术提供更好的区分信息。
