Tendon is a bradytrophic and hypovascular tissue, hence, healing remains a major challenge. The molecular key events involved in successful repair have to be unravelled to develop novel strategies that reduce the risk of unfavourable outcomes such as non-healing, adhesion formation, and scarring. This review will consider the diverse pathophysiological features of tendon-derived cells that lead to failed healing, including misrouted differentiation (e.g. de- or transdifferentiation) and premature cell senescence, as well as the loss of functional progenitors. Many of these features can be attributed to disturbed cell-extracellular matrix (ECM) or unbalanced soluble mediators involving not only resident tendon cells, but also the cross-talk with immigrating immune cell populations. Unrestrained post-traumatic inflammation could hinder successful healing. Pro-angiogenic mediators trigger hypervascularization and lead to persistence of an immature repair tissue, which does not provide sufficient mechano-competence. Tendon repair tissue needs to achieve an ECM composition, structure, strength, and stiffness that resembles the undamaged highly hierarchically ordered tendon ECM. Adequate mechano-sensation and -transduction by tendon cells orchestrate ECM synthesis, stabilization by cross-linking, and remodelling as a prerequisite for the adaptation to the increased mechanical challenges during healing. Lastly, this review will discuss, from the cell biological point of view, possible optimization strategies for augmenting Achilles tendon (AT) healing outcomes, including adapted mechanostimulation and novel approaches by restraining neoangiogenesis, modifying stem cell niche parameters, tissue engineering, the modulation of the inflammatory cells, and the application of stimulatory factors. Cite this article:
To develop an early implant instability murine model and explore the use of intermittent parathyroid hormone (iPTH) treatment for initially unstable implants. 3D-printed titanium implants were inserted into an oversized drill-hole in the tibiae of C57Bl/6 mice (n = 54). After implantation, the mice were randomly divided into three treatment groups (phosphate buffered saline (PBS)-control, iPTH, and delayed iPTH). Radiological analysis, micro-CT (µCT), and biomechanical pull-out testing were performed to assess implant loosening, bone formation, and osseointegration. Peri-implant tissue formation and cellular composition were evaluated by histology.Aims
Methods
Aims. Despite the interest in the association of gut microbiota with bone health, limited population-based studies of gut microbiota and bone mineral density (BMD) have been made. Our aim is to explore the possible association between gut microbiota and BMD. Methods. A total of 3,321 independent loci of gut microbiota were used to calculate the individual polygenic risk score (PRS) for 114 gut microbiota-related traits. The individual genotype data were obtained from UK Biobank cohort. Linear regressions were then conducted to evaluate the possible association of gut microbiota with L1-L4 BMD (n = 4,070), total BMD (n = 4,056), and femur total BMD (n = 4,054), respectively. PLINK 2.0 was used to detect the single-nucleotide polymorphism (SNP) × gut microbiota interaction effect on the risks of L1-L4 BMD, total BMD, and femur total BMD, respectively. Results. We detected five, three, and seven candidate gut microbiota-related traits for L1-L4 BMD, total BMD, and femur BMD, respectively, such as genus Dialister (p = 0.004) for L1-L4 BMD, and genus Eisenbergiella (p = 0.046) for total BMD. We also detected two common gut microbiota-related traits shared by L1-L4 BMD, total BMD, and femur total BMD, including genus Escherichia Shigella and genus Lactococcus. Interaction analysis of BMD detected several genes that interacted with gut microbiota, such as phospholipase D1 (PLD1) and
Aims. It is increasingly appreciated that coordinated regulation of angiogenesis and osteogenesis is needed for bone formation. How this regulation is achieved during peri-implant bone healing, such as osseointegration, is largely unclear. This study examined the relationship between angiogenesis and osteogenesis in a unique model of osseointegration of a mouse tibial implant by pharmacologically blocking the vascular endothelial growth factor (VEGF) pathway. Materials and Methods. An implant was inserted into the right tibia of 16-week-old female C57BL/6 mice (n = 38). Mice received anti-VEGF receptor-1 (VEGFR-1) antibody (25 mg/kg) and VEGF receptor-2 (VEGFR-2) antibody (25 mg/kg; n = 19) or an isotype control antibody (n = 19). Flow cytometric (n = 4/group) and immunofluorescent (n = 3/group) analyses were performed at two weeks post-implantation to detect the distribution and density of CD31. hi. EMCN. hi. endothelium. RNA sequencing analysis was performed using sorted CD31. hi. EMCN. hi. endothelial cells (n = 2/group). Osteoblast lineage cells expressing osterix (OSX) and osteopontin (OPN) were also detected with immunofluorescence. Mechanical pull-out testing (n = 12/group) was used at four weeks post-implantation to determine the strength of the bone-implant interface. After pull-out testing, the tissue attached to the implant surface was harvested. Whole mount immunofluorescent staining of OSX and OPN was performed to determine the amount of osteoblast lineage cells. Results. Flow cytometry revealed that anti-VEGFR treatment decreased CD31. hi. EMCN. hi. vascular endothelium in the peri-implant bone versus controls at two weeks post-implantation. This was confirmed by the decrease of CD31 and
