This study aimed to analyze if the sensory neuropeptide SP (SP) and the neurokinin receptor 1 (NK1R) are involved in macrophage mechano-transduction, similar to chondrocytes, and if alpha-calcitonin gene-related peptide (αCGRP) and the CGRP receptor (CRLR/Ramp1) show comparable activity. Murine RAW264.7 macrophages were subjected to a cyclic stretch for 1–3 days and 4 h/day. Loading and neuropeptide effects were analyzed for gene and protein expression of neuropeptides and their receptors, adhesion, apoptosis, proliferation and ROS activity. Murine bone marrow-derived macrophages (BMM) were isolated after surgical osteoarthritis (OA) induction and proliferation, apoptosis and osteoclastogenesis were analyzed in response to loading. Loading induced NK1R and CRLR/Ramp1 gene expression and altered protein expression in RAW264.7 macrophages. SP protein and mRNA level decreased after loading whereas αCGRP mRNA expression was stabilized. SP reduced adhesion in loaded RAW264.7 macrophages and both neuropeptides initially increased the ROS activity followed by a time-dependent suppression. OA induction sensitized BMM to caspase 3/7 mediated apoptosis after loading. Both sensory neuropeptides, SP and αCGRP, and their receptors are involved in murine macrophage mechano-transduction affecting neuropeptide impact on adhesion and ROS activity. OA induction altered BMM apoptosis in response to loading indicate that OA-associated biomechanical alterations might affect the macrophage population.

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Purpose: There is strong evidence to suggest altered knee biomechanics and aberrant joint tissue biology are associated with the development and progression of knee osteoarthritis (OA), however our understanding of the link between mechanics and biology in humans with knee pathology is lacking. Human biomechanics studies have shown a link of medial knee OA to knee varus malalignment and increased medial knee compartment loading. Furthermore, changes in bone structure and inflammation are thought to be responsible for long term joint deterioration. We hypothesized that joint inflammation and altered bone remodeling in the degenerative knee are a consequence of medial knee overloading. Therefore, this study aimed to determine if indicators of dynamic frontal plane knee loading or knee varus alignment are associated with synovial fluid biomarkers of joint inflammation, altered bone turnover or bone mechanobiology in subjects with medial knee degeneration. Methods: Subjects with medial knee OA (KL grade II-IV) undergoing high tibial osteotomy surgery or isolated medial knee ICRS grade III focal cartilage defects undergoing microfracture surgery had synovial fluid (SF) aspirated from the affected knee and underwent 3D motion capture analysis within a 4-week period. Kinematic marker data and ground reaction forces from level barefoot walking at a self-selected pace were measured using a 12 infra-red camera (Qualisys) and 6 force plate (Bertec) set up, with a modified Helen Hayes marker-set. A six-degrees-of-freedom musculoskeletal model with 8 segments was built (Visual 3D) to calculate early-and late-stance peak knee adduction moments (1 st peak and 2 nd peak KAMs, respectively) representative of peak medial knee compartmental loading, knee adduction angles during KAM peaks (1 st peak and 2 nd peak KAAs) representative of dynamic joint alignment during peak loads, and the knee adduction angular impulse (KAAI) representative of cumulative medial knee loading over stance-phase. SF aspirated from the affected knee was centrifuged at 5000G for 15m to remove cells and stored at -80 C. Multiplex chemiluminescence (Mesoscale Discovery) or enzyme-linked immunosorbent assays quantified the concentrations of 10 SF molecules relating to inflammation (proinflammatory: TNF-a, IL-6, IL-8; anti-inflammatory: IL-10), bone remodeling (formation: ALP, OPG; resorption: CTX-I, RANKL) and bone mechanobiology (glutamate, sclerostin). The RANKL:OPG ratio was also calculated as an indication of osteoclast activity. Normality of biomarker data was tested using Shapiro Wilks Test. Non-normal biomarker data was log-transformed prior to regression to satisfy assumptions. Multiple regression was applied to predict biomarker levels from biomechanical parameters, whilst controlling for age and BMI as covariates.Results: Biomechanical and biological data was collected from 10 medial knee pathology subjects (all male; mean (SD) age ¼ 50.3 (6.2) years, BMI ¼ 28.7 (3.9) kg/m 2 ). For the effect of knee mechanics on inflammatory markers, 2 nd peak KAMs ...

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