Multiscale characterization of cortical bone composition, microstructure, and nanomechanical properties in experimentally induced osteoporosis

Abstract

Cortical bone plays a vital role in determining overall bone strength. We investigate the structural, compositional, and nanomechanical properties of cortical bone following ovariectomy (OVX) of 12-week-old Sprague Dawley rats, since this animal model is frequently employed to evaluate the performance of implantable biomaterials in compromised bone healing conditions. Morphological parameters and material properties of bone in the geometrical center of the femoral cortex were investigated four and eight weeks post-OVX and in unoperated controls (Ctrl), using X-ray micro-computed tomography, backscattered electron scanning electron microscopy, Raman spectroscopy, and nanoindentation. The OVX animals showed increase in body weight, diminished bone mineral density, increased intracortical porosity, but increased bone mass through periosteal apposition (e.g., increases in periosteal perimeter, cortical cross-sectional thickness, and cross-sectional area). However, osteocyte densities, osteocyte lacunar dimensions, and the nanomechanical behavior on the single mineralized collagen fibril level remained unaffected. Our correlative multiscale investigation provides structural, chemical, and nanomechanical evidence substantiating earlier reports suggesting that rats ovariectomized at 12 weeks undergo simultaneous bone loss and growth, resulting in the effects of OVX being less obvious. Periosteal apposition contradicts the conventional view of bone loss in osteoporosis but appears advantageous for the greater functional demand imposed on the skeleton by increased body weight and fragility induced by increased intracortical porosity. Through a variety of morphological changes, it is likely that 12-week-old rats are able to adapt to OVX-related microstructural and compositional alterations. © 2017 Wiley Periodicals, Inc. J Biomed Mater Res Part A: 106A: 997-1007, 2018.

Sequential Treatment of Estrogen Deficient, Osteopenic Rats with Alendronate, Parathyroid Hormone (1–34), or Raloxifene Alters Cortical Bone Mineral and Matrix Composition

“…If an osteoporosis treatment agent were to change bone tissue composition in remodeling bone tissue, but not in non-remodeling tissue, one would not only know that it acts by affecting bone remodeling activity, but could also legitimately speculate that they it does not affect other tissue level mechanisms like osteocyte activity. Our data, like many [28,41,42], but not others [43], show no differences in composition of cortical bone between Sham-OVX and OVX rats. On the other hand, data from non-human primate cortical bone remodeling sites, show that bone tissue composition differs in OVX and Sham-OVX animals in a bone site where both remodeling activity and osteocyte activity are ongoing [44,45].…”

Bone Response to Dietary Co-Enrichment with Powdered Whole Grape and Probiotics

“…Age-related decreases in cortical bone thickness due to expansion of the medullary region have been reported by some [ 49 , 100 ], but not all [ 59 ], investigators. In ovariectomized rodents, cortical bone thickness has been shown to decline [ 97 ], increase [ 101 ], or remain unchanged [ 102 ]. Despite these differences, it is notable that polyphenol-rich fruit consumption has produced beneficial bone responses in both models of osteoporosis [ 37 , 49 , 57 , 103 ].…”

Does Smoking Impair Bone Regeneration in the Dental Alveolar Socket?

“…Here, Phe levels for Smokers (12-32%) and Ctrl (8-33%) were relatively higher, which reflects the contribution of rapidly formed woven bone. Pro + Hyp content also declines with tissue age [29], but did not differ between the two groups.…”

“…Low Z-(atomic number) contrast features arising from the embedding medium were removed by applying a mean filter (radius = 1 pixel) followed by image segmentation using the Otsu algorithm in ImageJ (https :// image j.nih.gov/ij/). From the greyscale (8-bit) histogram of each sample, the degree of mineralisation (dMn) was estimated as a dimensionless parameter, by integrating the product of each greyscale intensity, i, and the corresponding pixel count, for all values of i (where 0 < i ≤ 255), divided by the total number of pixels [29]. Mineralisation profiles were obtained from greyscale histograms.…”