Fig Ex.1: Experimental design to evaluate bone anabolism in OI mice. [unpublished]
Fig Ex.2: Experimental design to evaluate cardiovascular risks in OI-ApoE-/- mice. [unpublished]
Fig Ex.3: Experimental design to evaluate bone anabolism in OI mice with human sclerostin. [unpublished]
We have devised a number of experimental protocols for our investigation, presented as follows.
Analysis of the trabecular bone at the left distal femoral metaphysis, the left proximal tibia metaphysis and the fourth lumbar vertebrae, as well as the cortical bone at the left femoral mid-shaft is performed with micro-CT[1].
Images of femur, tibia, and vertebrae will be reconstructed and calibrated at the isotropic voxel size of 12.5 and 17.5 μm, respectively[2]. Every measurement uses the same filtering and segmentation values. Using the Scanco evaluation software, regions of interest will be defined for both trabecular and cortical parameters.
For trabecular bones, a central region will be selected equivalent to 70% of the vertebral body height and extended from proximally to the end of the distal growth plate toward the vertebral body. We drew freehand the trabeculae regions of interest on 100 sequential slices to ensure it will be within the endosteal envelope. Trabecular bone parameters, including trabecular volume per total volume (Tb.BV/TV), trabecular volumetric bone mineral density (Tb.vBMD), trabecular thickness (Tb.Th), trabecular number (Tb.N), trabecular spacing (Tb.Sp), trabecular structure model index (Tb.SMI) and trabecular connectivity density (Tb.conn.D) will be calculated.
For cortical bones, 100 slices will be measured at the exact center and at the distal 50% of femur length using the automated thresholding algorithm. Trabeculae in contact with cortical bone will be manually removed from the regions of interest. Cortical bone parameters, including cortical volumetric bone mineral density (Ct.vBMD) and cortical thickness (Ct.Th) will be calculated[a].
After sacrificing, the left distal femoral metaphysis, the left proximal tibial metaphysis and the fifth lumbar vertebrae, as well as the left femoral mid-shaft will be fixed in 4% Paraformaldehyde for 48 h, dehydrated in an increased 10%, 20%, 30% concentrations of sucrose (dilution in 1x PBS) for 24 h in each concentration and embedded without decalcification in an optimal cutting temperature compound[3].
After embedding, the proximal region of the samples will be sectioned longitudinally, and the histomorphometric analyses of trabecular bone will be performed at the above four sites. The frozen tissue specimens will be obtained at a thickness of 5 μm with CryoStar NX50[4].
The sites will be consistent with the selected sites of Micro-CT. Fluorescence micrographs for the bone sections will be captured by a Q500MC fluorescence microscope[5]. The parameters of bone dynamic histomorphometric analysis for trabecular bone and cortical bone includes bone formation rate (BFR/BS) and mineral apposition rate (MAR).
The analysis will be performed using a professional histomorphometric analysis system[6] and the parameters will be calculated and expressed according to the ASBMR standardized nomenclature for bone histomorphometry[b].
The fifth lumbar vertebra (Lv5) and the right femora will be used to describe the bone mechanical properties through the compression test and the three-point test by using a universal testing machine[7] with a 2.5 kN load cell.
For compression tests, Lv5s will be isolated from vertebral columns and constructed into a cylinder with two parallel planes (5-7 cm) before the test. The Lv5s will be positioned horizontally to the base. Load are applied constantly with displacement rate of 1 mm/min. After failure, the load vs. displacement curves will be recorded and the failure force (N) and ultimate strength (MPa) will be calculated for statistical analysis.
For three-point tests, femora will be loaded in the anterior-posterior direction with the span set as 5 mm. Load will be applied with a constant displacement rate of 1 mm/min at the femur mid-shaft. After failure, the load vs. displacement curves will be recorded and the failure force (N), stiffness and fracture energy (J) will be calculated for statistical analysis.
The concentration of inflammatory cytokines (IL-6, TNFα) and chemokines (MCP-1) in serum of mice were determined by ELISA kit[8] in triplicate following manufacturer’s instructions[c].
Immediately after sacrifice, the aortas were perfused via left ventricle with ice-cold saline, isolated from the fat and connective tissues under Zeiss Stemi 305 Stereomicroscope with AxioCam 208 Color Camera, and then fixed in 4% paraformaldehyde (PFA). The aortas with or without aneurysm formation were defined according to Daugherty's modified classification.
The incidence of AA of each group was determined as follows:
The maximum outer diameters of thoracic aorta and suprarenal aorta of each mouse were determined by Zeiss software[9; c, d].
The atherosclerotic plaque was quantified by measuring the surface area of the Oil Red O-positive lesions on en face preparation of aortic arches. In addition, the saline-perfused upper half of the heart including the aortic root was directly embedded in an optimal cutting temperature compound[10], frozen in liquid nitrogen, and cryo-sectioned (10 μm).
The ratio of atherosclerotic plaque area to total cross cryo-section area of aortic root was examined by Oil Red O staining, and quantified by colorimetric analysis using Image J software[c, d].
[1] Version 6.5, vivaCT40, SCANCO Medical AG, Bassersdorf, Switzerland. [2] 70 kVp, 114 μA, 200 ms integration time, 260 thresholds, 1200 mg HA/cm3. [3] Sakura Finetek, Co. Ltd., Tokyo, Japan. [4] Thermo Fisher Scientific, Waltham, MA, USA. [5] Leica, Bensheim, Germany. [6] BIOQUANT OSTEO, Nashville, TN, USA. [7] H25KS Series, Hounsfield Test Equipment Ltd, Redhill, UK. [8] eBioscience. [9] Carl Zeiss Far East Co., Ltd., Germany. [10] O.C.T., Sakura Finetek, Co. Ltd., Tokyo, Japan. [a] Zhang, Guo et al. 2012, Liang, Guo et al. 2015. [b] Li, Liu et al. 2016. [c] Krishna, Seto et al. 2017. [d] Zong-Kang Zhang, 2016.
