br Alu qPCR analysis for MSC homing br

2.16. Alu qPCR analysis for MSC homing
Whole legs were harvested after euthanasia, stripped down to a thin layer of muscle surrounding the bones (muscle prevents loss of fragilised bones fragments), and flash frozen in slurry of 70% ethanol and dry ice. Surgical tools were cleaned in between each leg to prevent cross contaminations. Tissues were thawed and immediately homogenised with mechanical force using metal bead agitation at 4 °C (Next Advance Bullet Blender® Storm with Navy 5 mL Lysis Kit). DNA extraction was performed on 25 mg of homogenised tissues (1/28th of the initial lysate) using chemical lysis and silica spin column purification (Qiagen DNeasy® Blood and Tissue Kit).
To quantify human MSC numbers in each mouse leg, an Alu qPCR assay was performed on 50 ng of extracted DNA using PowerUp™ SYBR™ Green Master Mix (Applied Biosystems, Dun Laoghaire, Ireland), optimised primer sets for the human Alu transposable G-418 (FWD: CACCTGTAATCCCAGCACTTT and REV: CCCAGGCTGGAGTGCAGT) [39], and the mouse GAPDH gene as an endogenous control (FWD: TGGCCTTCCGTGTTCCTAC and REV: GAGTTGCTGTTGAAGTCGCA) [40]. A QuantStudio™ 6 Flex Real-Time PCR System was used to run the qPCR, and data were analysed using QuantStudio™ 6 and 7 Flex Real-Time PCR System Software (Applied Biosystems, Dun Laoghaire, Ireland). A comparative CT value ( CT) for human MSC in each tissue was derived by subtracting the mean of triplicate mGAPDH CT values from the mean of triplicate hAlu CT values [41].
A standard curve was established by injecting known quantities of MSC into the tibias of BALB/cJ mice following 6 fold serial dilutions of the cell suspension (100, 600, 3600, 21,600 and 130,000 MSC), followed by tissue homogenisation/DNA extraction/qPCR (as described above). The logarithm of the number of MSC injected was plotted versus the
CT, and a linear regression was done to generate a standard curve slope equation. Cell numbers in each sample leg were calculated by the standard curve equation from the obtained CT value. The limit of detection was determined by subtracting 2 from the negative control (PBS injection only in the mouse tibia) CT value [42].
2.17. Bone micro-computed analysis and bone damage scoring
Mouse tibias were fixed in 4% PFA for 48 h immediately after dissection. After tissue fixation, samples were transferred to a radiotransparent container in sterile PBS. For our initial study, 3D X-Ray imaging was performed using VersaXRM™410 (Xradia, Pleasanton, CA, USA) with 14 μm voxel size. 3D volumes for whole tibias and trabec-ular bone were reconstructed into DICOM files for segmentation using ScanIP software (Ver. 7.0, Simpleware Ltd). ROIs were defined as the fol-lowing: 1) epiphysis of the tibia down to the fibula insertion point for the whole tibia reconstruction, and 2) 100 slices (1.4 mm total) starting below the growth plate down to the diaphysis where trabeculae disap-pear for the trabecular bone reconstruction. Bone was segmented from the background using grayscale values, and a mask was generated from that thresholding to reconstruct the whole tibia via a built-in rendering function, followed by whole tibia smoothing using a “Recursive Gauss-ian” filter with cubic values of 2.0 cm. For trabecular reconstructions, a second ROI was generated on 2D slices after thresholding to outline the trabecular cavity and exclude the cortical bone. The morphological “Close” function was then used to fill the space in between outlines, thus generating a first mask, filling the cavity of the tibia. A “Multilevel Otsu segmentation” was applied to generate a second mask which encompassed only the background, excluding the trabecular bone. To generate a 3D trabecular bone model, a built-in rendering function was applied to a final mask resulting from the subtraction of the second mask from the first mask.
For our final studies, femur or tibia samples were imaged on a micro-Computed Tomography scanner, Skyscan 1076 (Bruker, Kontich, Belgium) at (9 μm)3 voxel size, 50 kVp, 200 μA and using a 0.5 mm alu-minium filter. Image reconstruction was performed with NRecon 
software (Bruker, Kontich, Belgium) using a beam-hardening correction algorithm, at a setting of 40% and a ring artefact reduction size of 8. Sam-ples were aligned vertically with Dataviewer software (Bruker, Kontich, Belgium). As reference points, the tips of the proximal tibial growth plate and distal femoral growth plate were noted. Then, using a custom method, an overview of each sample was visualised as 15 transverse 2D sections spaced every ~140 μm. In addition, CTvox software (Bruker, Kontich, Belgium) used with a global threshold value that selected the majority of cortical bone outline and trabecular bone to make 3D ren-ders. Total bone volume and trabecular bone volume were analysed across 900 μm (100 slices), starting 180–360 μm from the reference point of the selected growth plate. The total bone was selected by man-ual contouring with elliptical cross-sections, encompassing the perios-teal tissue and the marrow cavity. A global threshold was used to identify total bone and an erosion of 1–2 pixel was performed to elimi-nate partial volume effects. The trabecular region, inward ~100 μm from the cortex, was selected by an automated contouring routine or else by manual tracing every ~20 slices with automated interpolation. An adap-tive threshold (using the mean maximum and minimum pixel intensity values of the surrounding ten pixels) was used to identify trabecular bone. The bone volume (BV) was determined using CTan (Bruker, Kontich, Belgium). For the femurs, analysis of the total BV was per-formed for the entirety of the femur bones.