The relationship of degeneration to symptoms has been questioned. MRI detects apparently similar disc degeneration and degenerative changes in subjects both with and without back pain. We aimed to overcome these problems by re-annotating MRIs from asymptomatic and symptomatic groups onto the same grading system. We analysed disc degeneration in pre-existing large MRI datasets. Their MRIs were all originally annotated on different scales. We re-annotated all MRIs independent of their initial grading system, using a verified, rapid automated MRI annotation system (SpineNet) which reported degeneration on the Pfirrmann (1-5) scale, and other degenerative features (herniation, endplate defects, marrow signs, spinal stenosis) as binary present/absent. We compared prevalence of degenerative features between symptomatics and asymptomatics. Pfirrmann degeneration grades in relation to age and spinal level were very similar for the two independent groups of symptomatics over all ages and spinal levels. Severe degenerative changes were significantly more prevalent in discs of symptomatics than asymptomatics in the caudal but not the rostral lumbar discs in subjects < 60 years. We found high co-existence of degenerative features in both populations. Degeneration was minimal in around 30% of symptomatics < 50 years. We confirmed age and disc level are significant in determining imaging differences between asymptomatic and symptomatic populations and should not be ignored. Automated analysis, by rapidly combining and comparing data from existing groups with MRIs and information on LBP, provides a way in which epidemiological and ‘big data’ analysis could be advanced without the expense of collecting new groups

To detect early signs of infection infrared thermography has been suggested to provide quantitative information. Our vision is to invent a pin site infection thermographic surveillance tool for patients at home. A preliminary step to this goal is the aim of this study, to automate the process of locating the pin and detecting the pin sites in thermal images efficiently, exactly, and reliably for extracting pin site temperatures. A total of 1708 pin sites was investigated with Thermography and augmented by 9 different methods in to totally 10.409 images. The dataset was divided into a training set (n=8325), a validation set (n=1040), and a test set (n=1044) of images. The Pin Detection Model (PDM) was developed as follows: A You Only Look Once (YOLOv5) based object detection model with a Complete Detection Intersection over Union (CDIoU), it was pre-trained and finetuned by the through transfer learning. The basic performance of the YOLOv5 with CDIoU model was compared with other conventional models (FCOS and YOLOv4) for deep and transition learning to improve performance and precision. Maximum Temperature Extraction (MTE) Based on Region of Interest (ROI) for all pin sites was generated by the model. Inference of MTE using PDM with infected and un-infected datasets was investigated. An automatic tool that can identify and annotate pin sites on conventional images using bounding boxes was established. The bounding box was transferred to the infrared image. The PMD algorithm was built on YOLOv5 with CDIoU and has a precision of 0.976. The model offers the pin site detection in 1.8 milliseconds. The thermal data from ROI at the pin site was automatically extracted. These results enable automatic pin site annotation on thermography. The model tracks the correlation between temperature and infection from the detected pin sites and demonstrates it is a promising tool for automatic pin site detection and maximum temperature extraction for further infection studies. Our work for automatic pin site annotation on thermography paves the way for future research on infection assessment using thermography

Aim. Osteoarthritis (OA) is caused by complex interactions between genetic and environmental factors. Epigenetic mechanisms control the expression of genes and are likely to regulate the OA transcriptome. We performed integrative genomic analyses to define methylation-gene expression relationships in osteoarthritic cartilage. Patients and Methods. Genome-wide DNA methylation profiling of articular cartilage from five patients with OA of the knee and five healthy controls was conducted using the Illumina Infinium HumanMethylation450 BeadChip (Illumina, San Diego, California). Other independent genome-wide mRNA expression profiles of articular cartilage from three patients with OA and three healthy controls were obtained from the Gene Expression Omnibus (GEO) database. Integrative pathway enrichment analysis of DNA methylation and mRNA expression profiles was performed using integrated analysis of cross-platform microarray and pathway software. Gene ontology (GO) analysis was conducted using the Database for Annotation, Visualization and Integrated Discovery (DAVID). Results. We identified 1265 differentially methylated genes, of which 145 are associated with significant changes in gene expression, such as DLX5, NCOR2 and AXIN2 (all p-values of both DNA methylation and mRNA expression < 0.05). Pathway enrichment analysis identified 26 OA-associated pathways, such as mitogen-activated protein kinase (MAPK) signalling pathway (p = 6.25 × 10-4), phosphatidylinositol (PI) signalling system (p = 4.38 × 10-3), hypoxia-inducible factor 1 (HIF-1) signalling pathway (p = 8.63 × 10-3 pantothenate and coenzyme A (CoA) biosynthesis (p = 0.017), ErbB signalling pathway (p = 0.024), inositol phosphate (IP) metabolism (p = 0.025), and calcium signalling pathway (p = 0.032). Conclusion. We identified a group of genes and biological pathwayswhich were significantly different in both DNA methylation and mRNA expression profiles between patients with OA and controls. These results may provide new clues for clarifying the mechanisms involved in the development of OA. Cite this article: A. He, Y. Ning, Y. Wen, Y. Cai, K. Xu, Y. Cai, J. Han, L. Liu, Y. Du, X. Liang, P. Li, Q. Fan, J. Hao, X. Wang, X. Guo, T. Ma, F. Zhang. Use of integrative epigenetic and mRNA expression analyses to identify significantly changed genes and functional pathways in osteoarthritic cartilage. Bone Joint Res 2018;7:343–350. DOI: 10.1302/2046-3758.75.BJR-2017-0284.R1

Introduction. The two-dimensional (2D) monolayer culture paradigm has limited translational potential to physiological systems; chondrocytes and tenocytes in monolayer lose expression of hallmarks of differentiated status (dedifferentiation). Qualitative assessment of three-dimensional (3D) cultures in musculoskeletal biology relative to native tissues has been limited. An understanding of prevailing gene regulatory networks is required to define whether 3D culture systems faithfully restitute the native tissue phenotype (redifferentiation). Using a systems biology approach to explore the gene networks associated with de- and re-differentiation may define targetable regulators associated with phenotypic plasticity of adult musculoskeletal cells. Materials and Methods. Global transcriptomic and proteomic profiling of matrix-depleted chondrocytes and tenocytes from the rat was performed for each of three conditions (native tissue, monolayer at passage three, or tissue-appropriate 3D cultures). Differential analysis of mRNA and protein abundance, gene ontology annotation, pathway topology impact analysis, and derivation of common mechanistic networks was undertaken to define consensus expression profiles, signalling pathways, and upstream regulators for de- and re-differentiation in each cell type. Results. Principal component analysis demonstrated a convergence of gene expression profiles in monolayer, including the expression of musculoskeletal progenitor markers scleraxis (Scx) and Mohawk (Mkx). Three-dimensional culture systems failed to demonstrate parity with native tissue and incited the expression of Il-6 and Ptgs2 (COX2). The CCN-family member Ctgf (CCN2), and the marker of skeletal differentiation Grem1 (gremlin 1), were consistently differentially abundant in de- and re-differentiation at both the mRNA and protein level. Pathway topology impact analysis defined PI-3K/Akt as the common signalling pathway in de- and re-differentiation. Discussion. Historically, the terms de- and re-differentiation have been used with no mechanistic definition. Additionally, there is no standardised phenotype for 3D cultures to benchmark novel progress in bioengineering. Consensus upstream regulators yielded a unified mechanistic network for chondrocyte and tenocyte phenotypes in three conditions. The PI-3K/Akt signalling pathway has been implicated in a range of physiological activities including dedifferentiation, proliferation, matrix synthesis, and cell survival. Pathway analysis suggests that the PI-3K/Akt signalling pathway may contribute to the de- and re-differentiation phenotypes for both chondrocytes and tenocytes and represents a rational target for further network-level analysis

Objectives

Several genome-wide association studies (GWAS) of bone mineral density (BMD) have successfully identified multiple susceptibility genes, yet isolated susceptibility genes are often difficult to interpret biologically. The aim of this study was to unravel the genetic background of BMD at pathway level, by integrating BMD GWAS data with genome-wide expression quantitative trait loci (eQTLs) and methylation quantitative trait loci (meQTLs) data

Objectives

In order to screen the altered gene expression profile in peripheral blood mononuclear cells of patients with osteoporosis, we performed an integrated analysis of the online microarray studies of osteoporosis.