Browsing by Author "Knox, Adam M."

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    Characterization and assessment of lung and bone marrow derived endothelial cells and their bone regenerative potential
    (Frontiers, 2022) de Lima Perini, Mariana Moraes; Valuch, Conner R.; Dadwal, Ushashi C.; Awosanya, Olatundun D.; Mostardo, Sarah L.; Blosser, Rachel J.; Knox, Adam M.; McGuire, Anthony C.; Battina, Hanisha L.; Nazzal, Murad; Kacena, Melissa A.; Li, Jiliang; Biology, School of Science
    Angiogenesis is important for successful fracture repair. Aging negatively affects the number and activity of endothelial cells (ECs) and subsequently leads to impaired bone healing. We previously showed that implantation of lung-derived endothelial cells (LECs) improved fracture healing in rats. In this study, we characterized and compared neonatal lung and bone marrow-derived endothelial cells (neonatal LECs and neonatal BMECs) and further asses3sed if implantation of neonatal BMECs could enhance bone healing in both young and aged mice. We assessed neonatal EC tube formation, proliferation, and wound migration ability in vitro in ECs isolated from the bone marrow and lungs of neonatal mice. The in vitro studies demonstrated that both neonatal LECs and neonatal BMECs exhibited EC traits. To test the function of neonatal ECs in vivo, we created a femoral fracture in young and aged mice and implanted a collagen sponge to deliver neonatal BMECs at the fracture site. In the mouse fracture model, endochondral ossification was delayed in aged control mice compared to young controls. Neonatal BMECs significantly improved endochondral bone formation only in aged mice. These data suggest BMECs have potential to enhance aged bone healing. Compared to LECs, BMECs are more feasible for translational cell therapy and clinical applications in bone repair. Future studies are needed to examine the fate and function of BMECs implanted into the fracture sites.
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    Methodology, selection, and integration of fracture healing assessments in mice
    (Wiley, 2021-11) Knox, Adam M.; McGuire, Anthony C.; Natoli, Roman M.; Kacena, Melissa A.; Collier, Christopher D.; Orthopaedic Surgery, School of Medicine
    Long bone fractures are one of the most common and costly medical conditions encountered after trauma. Characterization of the biology of fracture healing and development of potential medical interventions generally involves animal models of fracture healing using varying genetic or treatment groups, then analyzing relative repair success via the synthesis of diverse assessment methodologies. Murine models are some of the most widely used given their low cost, wide variety of genetic variants, and rapid breeding and maturation. This review addresses key concerns regarding fracture repair investigations in mice and may serve as a guide in conducting and interpreting such studies. Specifically, this review details the procedures, highlights relevant parameters, and discusses special considerations for the selection and integration of the major modalities used for quantifying fracture repair in such studies, including X-ray, microcomputed tomography, histomorphometric, biomechanical, gene expression and biomarker analyses.
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    Validation of the modified radiographic union score for tibia fractures (mRUST) in murine femoral fractures
    (Frontiers Media, 2022-08-03) Alentado, Vincent J.; Knox, Adam M.; Staut, Caio A.; McGuire, Anthony C.; Chitwood, Joseph R.; Mostardo, Sarah L.; Shaikh, Mustufa Z.; Blosser, Rachel J.; Dadwal, Usashi C.; Chu, Tien-Min Gabriel; Collier, Christopher D.; Li, Jiliang; Liu, Ziyue; Kacena, Melissa A.; Natoli, Roman M.; Neurological Surgery, School of Medicine
    Bony union is a primary predictor of outcome after surgical fixation of long bone fractures. Murine models offer many advantages in assessing bony healing due to their low costs and small size. However, current fracture recovery investigations in mice frequently rely on animal sacrifice and costly analyses. The modified Radiographic Union Score for Tibia fractures (mRUST) scoring system is a validated metric for evaluating bony healing in humans utilizing plain radiographs, which are relatively inexpensive and do not require animal sacrifice. However, its use has not been well established in murine models. The aim of this study was to characterize the longitudinal course of mRUST and compare mRUST to other conventional murine fracture analyses. 158 mice underwent surgically created midshaft femur fractures. Mice were evaluated after fracture creation and at 7, 10, 14, 17, 21, 24, 28, 35, and 42 days post-injury. mRUST scoring of plain radiographs was performed by three orthopaedic surgeons in a randomized, blinded fashion. Interrater correlations were calculated. Micro-computed tomography (μCT) was analyzed for tissue mineral density (TMD), total callus volume (TV), bone volume (BV), trabecular thickness, trabecular number, and trabecular separation. Histomorphometry measures of total callus area, cartilage area, fibrous tissue area, and bone area were performed in a blinded fashion. Ultimate torque, stiffness, toughness, and twist to failure were calculated from torque-twist curves. A sigmoidal log-logistic curve fit was generated for mRUST scores over time which shows mRUST scores of 4 to 6 at 7 days post-injury that improve to plateaus of 14 to 16 by 24 days post-injury. mRUST interrater correlations at each timepoint ranged from 0.51 to 0.86, indicating substantial agreement. mRUST scores correlated well with biomechanical, histomorphometry, and μCT parameters, such as ultimate torque (r=0.46, p<0.0001), manual stiffness (r=0.51, p<0.0001), bone percentage based on histomorphometry (r=0.86, p<0.0001), cartilage percentage (r=-0.87, p<0.0001), tissue mineral density (r=0.83, p<0.0001), BV/TV based on μCT (r=0.65, p<0.0001), and trabecular thickness (r=0.78, p<0.0001), among others. These data demonstrate that mRUST is reliable, trends temporally, and correlates to standard measures of murine fracture healing. Compared to other measures, mRUST is more cost-effective and non-terminal. The mRUST log-logistic curve could be used to characterize differences in fracture healing trajectory between experimental groups, enabling high-throughput analysis.