The aim of this current study was to assess the effect of pathological mechanical load on the osteocyte signature. This will help identify mechanical mechanisms that cause pain or alter bone tissue structure in vitro and provide new mechanistic insight into disease progression. Y201 mesenchymal stem cells (MSCs) were differentiated in 3D collagen gels in silicone plates. Gels were loaded using a BOSE ElectroForce® 3200 loading instrument (TE Instruments, UK) to stretch the plate causing cyclic compression in all wells (pathophysiological load 4300με induced by 0.7mm displacement, 10Hz, 3000 cycles). Control gels in the silicone plate were placed into the loading device but received no load. RNA was harvested from gels 1 hour after load. RNA sequencing was carried out on n=4 control and n=5 loaded samples and differentially expressed genes identified using an DEseq2 analysis on normalised count data. The resultant p-values were corrected for multiple testing and false discovery issues using the FDR method.Mechanical loading of the osteocyte model regulated 7564 genes (Padj p<0.05, 3026 down, 4538 up). 93% of the osteocyte transcriptome signature was expressed in the model with 38% of these genes mechanically regulated. Mechanically loaded osteocytes regulated 26% of gene ontology pathways linked to OA pain, 40% reflecting bone remodelling and 27% representing inflammation.

The aim of this current study was to assess the effect of pathological mechanical load on the osteocyte signature. This will help identify mechanical mechanisms that cause pain or alter bone tissue structure in vitro and provide new mechanistic insight into disease progression. Y201 mesenchymal stem cells (MSCs) were differentiated in 3D collagen gels in silicone plates. Gels were loaded using a BOSE ElectroForce® 3200 loading instrument (TE Instruments, UK) to stretch the plate causing cyclic compression in all wells (pathophysiological load 4300με induced by 0.7mm displacement, 10Hz, 3000 cycles). Control gels in the silicone plate were placed into the loading device but received no load. RNA was harvested from gels 1 hour after load. RNA sequencing was carried out on n=4 control and n=5 loaded samples and differentially expressed genes identified using an DEseq2 analysis on normalised count data. The resultant p-values were corrected for multiple testing and false discovery issues using the FDR method.Mechanical loading of the osteocyte model regulated 7564 genes (Padj p<0.05, 3026 down, 4538 up). 93% of the osteocyte transcriptome signature was expressed in the model with 38% of these genes mechanically regulated. Mechanically loaded osteocytes regulated 26% of gene ontology pathways linked to OA pain, 40% reflecting bone remodelling and 27% representing inflammation.

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Additional file 1: Supplementary 1: Temperature Validation. Supplementary 2: Koyukuk males spline model results for elevation and temperature interaction. Supplementary 3: Interactive 3D plots of interaction between ambient temperature and canopy cover. Supplementary 4: Used-Available Tables of Covariates. Supplementary 5: Regional Habitat Features. Figure 1e: Regional variation in elevation. ANOVA results comparing regional variation in elevation show that all regions vary from each other statistically (F = 2705, p

Additional file 1: Supplementary 1: Temperature Validation. Supplementary 2: Koyukuk males spline model results for elevation and temperature interaction. Supplementary 3: Interactive 3D plots of interaction between ambient temperature and canopy cover. Supplementary 4: Used-Available Tables of Covariates. Supplementary 5: Regional Habitat Features. Figure 1e: Regional variation in elevation. ANOVA results comparing regional variation in elevation show that all regions vary from each other statistically (F = 2705, p