RNA-Seq or whole transcriptome shotgun sequencing has been adopted in the last years as a reference technique to determine the presence and the quantity of different species of RNA in determined biological samples, thanks to it allows the identification every single RNA species transcribed from a reference genome. Meta-profiling takes advantage of the public availability of an increasing set of RNA-Seq data produced by different laboratories to summarize the expression levels of the different RNA species of many samples according to their biological context, giving the opportunity to perform comparisons on the gene expression profiles of different tissues by integrating data derived from a high number of studies. By using Genevestigator™; a platform which integrates RNA-Seq data into meta-profiles, we have performed a comparison between the gene expression profiles of bone, cartilage, muscle tendon and skin by means of interrogating its database with different gene sets and families with relevance to the function of the tissues of the
Imaging of the
Osteoarthritis is the most prevalent joint disease, causing severe pain, deformity and a loss of mobility. Low back pain (LBP), frequently associated with degeneration of the intervertebral disc (IVD), is the No.1 cause of Years Lived with Disability. Age is a major risk factor for both conditions. However, the reasons why susceptibility to these conditions increases with age are poorly understood. The circadian (24 hourly) clocks in the brain and periphery direct key aspects of physiology through rhythmic control of tissue-specific sets of downstream genes. Work from our group focuses on the roles of circadian clocks in the articular cartilage and IVD. We show that the daily rhythm in these tissues becomes dampened and out-of-phase during ageing. Further, our data identify circadian clock disruption in cartilage and IVD as a new target of inflammation. Moreover, we show that mice with targeted knockout of an essential clock gene (BMAL1) in chondrocytes and disc cells have profound, yet tissue-specific degeneration in the articular cartilage and IVD. These findings implicate the local skeletal clock as a key regulatory mechanism for tissue homeostasis. This new avenue of research holds potential to better understand, and eventually treat these debilitating conditions.
X-ray is the standard method for monitoring fracture healing however it is not ideal; signs of healing are not normally visible on X-ray until around 6–8 weeks post fracture. Ultrasonography allows the detection of both the initial haematoma, usually formed immediately after fracture, and the small calcium deposits laid down between broken bone ends in the first stages of fracture healing. It has been reported that these early indicators of the healing process are visible as early as 1–2 weeks after fracture. We use Freehand 3D Ultrasound to monitor the early stages of fracture healing as both the bone surface and surrounding soft tissues can be imaged simultaneously. The Freehand 3D Ultrasound system consists of a standard Ultrasound machine, a PC running STRAD-WIN (Medical Imaging Group, Cambridge University) 3D software, and an optical tracking devise (NDI Polaris) to record the position and orientation of the Ultrasound probe during scanning. Images are transferred from the Ultrasound machine to the PC using RF capture through out a scan. Calibrating the system matches up the correct image with the correct probe position to produce a 3D dataset. We segment features of interest on the sequence of 2D images to construct a 3D model. These models are rotatable and provide views of the scanned anatomy that are not otherwise achievable using conventional Ultrasound or X-ray. The 3D data set can also be resliced through any plane to provide further views. To conduct a 3D Ultrasound scan takes the same amount of time as a conventional 2D scan. The production of the 3D model takes between 15–60 minutes depending on the level of detail required. Distances are measurable to within ±0.4mm meaning fracture gaps of sub-millimeter width can be resolved. The system has already been evaluated on healthy volunteers and a clinical study currently underway.
Granular Cell Tumours are rare mesenchymal soft tissue tumours that arise throughout the body and are believed to be of neural origin. They often present as an asymptomatic slow-growing benign solitary lesion but may be multifocal. One to two percent of cases are malignant and can metastasise. Described series in the literature are sparse. We examined our database and identified eleven cases in ten patients treated surgically and followed-up for a period of over six years (May 2002 to January 2009) in our regional bone and soft tissue tumour centre. Five tumours were located in the lower limb, four in the upper limb and two in the axial skeleton. Mean patient age was 31.2 years (range 8 to 55 years). Excision was complete in one case, marginal in five cases and intra-lesional in five cases. No specimens showed evidence of malignancy. No patients required postoperative adjuvant treatment. Mean follow-up was 19.3 months (range 1 to 37 months), with no cases of local recurrence. One case was multi-focal. Histopathological examination revealed the classical features of granular cell tumour in all cases. Typically, tumour cells were diffusely and strongly positive for S100 protein by immunohistochemistry, whereas the other markers tested were negative. We believe this case series to be the largest of its type in patients presenting to an orthopaedic soft tissue tumour unit. We present our findings and correlate it with findings of other series in the literature.
Developmental exposure to estrogens has been shown to affect a number of organ systems, including long and short bones. Epigenetic effects of DES exposure have been shown to affect the third generation of progeny. Furthermore, recent studies have shown that environmental exposure to estrogen-like compounds is much higher than originally anticipated. This study aims to discover the effect of in utero exposure to a well-known estrogen agonist, diethylstilbestrol (DES), on lumbar bone, intervertebral disc (IVD), and articular cartilage. Femoral bone was studied to determine the specificity of the effect. C57bl/6n pregnant mice were dosed orally with vehicle (peanut oil) or 0.1, 1.0 and 10 g/kg/day of DES on gestational days 11–14. Male and female pups were allowed to mature without further treatment until 3 months of age, at which point they were divided into swim and sedentary groups. After sacrifice, bone mineral density (BMD), bone mineral content (BMC), bone area (BA), and trabecular bone area (TBA) of the lumbar vertebrae and femur were measured using a PIXImus Bone Densitometer System (GE Medical Systems). Glycosaminoglycan (GAG) content (proteoglycan) was measured by the DMMB assay. Histological analysis of proteoglycan was performed with Safranin O staining. Intervertebral disc height was measured using NDP software (Leeds, UK). Statistical analysis was performed using analysis of variance (ANOVA) followed by Fisher's Protected Least Significant Difference (PLSD). A p-value of < 0.05 was considered statistically significant.Purpose
Method
Imaging can provide valuable information about the function of tissues and organs. The capacity for detecting and measuring imaging biomarkers of biological activities, allows for a better understanding of the pathophysiology of any process in the human body, including the
Aims. Tenosynovial giant cell tumour (TGCT) is a rare benign tumour of the
Our
Osteotomies in the
Geometric deep learning is a relatively new field that combines the principles of deep learning with techniques from geometry and topology to analyze data with complex structures, such as graphs and manifolds. In orthopedic research, geometric deep learning has been applied to a variety of tasks, including the analysis of imaging data to detect and classify abnormalities, the prediction of patient outcomes following surgical interventions, and the identification of risk factors for degenerative joint disease. This review aims to summarize the current state of the field and highlight the key findings and applications of geometric deep learning in orthopedic research. The review also discusses the potential benefits and limitations of these approaches and identifies areas for future research. Overall, the use of geometric deep learning in orthopedic research has the potential to greatly advance our understanding of the
Non-linear methods in statistical shape analysis have become increasingly important in orthopedic research as they allow for more accurate and robust analysis of complex shape data such as articulated joints, bony defects and cartilage loss. These methods involve the use of non-linear transformations to describe shapes, rather than the traditional linear approaches, and have been shown to improve the precision and sensitivity of shape analysis in a variety of applications. In orthopedic research, non-linear methods have been used to study a range of topics, including the analysis of bone shape and structure in relation to osteoarthritis, the assessment of joint deformities and their impact on joint function, and the prediction of patient outcomes following surgical interventions. Overall, the use of non-linear methods in statistical shape analysis has the potential to advance our understanding of the relationship between shape and function in the
Cerebral palsy (CP) is a neural condition that impacts and impairs the
In the context of regenerative medicine for the treatment of musculoskeletal pathologies mesenchymal stromal cells (MSCs) have shown good results thanks to secretion of therapeutic factors, both free and conveyed within the extracellular vesicles (EV), which in their totality constitute the “secretome”. The portfolio and biological activity of these molecules can be modulated by both in vitro and in vivo conditions, thus making the analysis of these activities very complex. A deep knowledge of the targets regulated by the secretome has become a matter of fundamental importance and a homogeneous and complete molecular characterization is still lacking in the field of applications for the
Spinal deformations are posture dependent. Official data from the Netherlands show that youth are encountering increasing problems with the
Introduction. Hip dysplasia is the most common congenital deformity of the
The human
Objectives. The aim of this study was to review the impact of smoking tobacco on the
Calcium is an important element for a wide range of physiological functions including muscle contraction, neuronal activity, exocytosis, blood coagulation and cell communication. In the
Objective. Modic changes (MC), a form of intervertebral disc degeneration visible as subchondral and vertebral bone marrow changes on spine magnetic resonance (MR), are known to be associated with low back pain. This study aimed to identify genes contributing to the development of MC using genome-wide association study. Methods. Presence of MC was evaluated in lumbar MR images in the Northern Finland Birth Cohort 1966 (NFBC1966, N=1182) and TwinsUK (N=647). Genome-wide association analyses were carried out in the cohorts separately using a linear regression model fitted to test for additive effects of SNPs and adjusting for age, sex, BMI, and either family relatedness via a kinship matrix (TwinsUK) or population stratification using principal components (NFBC1966). Meta-analysis of the two studies was carried out using the inverse-variance weighting approach. Results. A locus associated with MC reaching genome-wide significance (p<5e-8) was found on chromosome 9 with the lead SNP rs1934268 in intron 6 of the PTPRD gene. The SNP is located in the region of binding for a number of transcription factors which are involved in the development of the