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Identifying the prevalence of degenerative spinal pathologies and relevant demographic risk factors is important for understanding spine injury risk, prevention, treatment, and outcome, and for distinguishing acute injuries from degenerative pathologies. Prevalence data in the literature are often based on small-scale studies focused on a single type of pathology. This study evaluates the prevalence of diagnosis of selected degenerative spinal pathology diagnoses using Medicare insurance claim data in the context of published smaller-scale studies. In addition, the data are used to evaluate whether the prevalence is affected by age, sex, diagnosed obesity, and the use of medical imaging. The Medicare Claims 5% Limited Data Set was queried to identify diagnoses of degenerative spinal pathologies. Unique patient diagnoses per year were further evaluated as a function of age, gender, and obesity diagnosis. Participants were also stratified by coding for radiological imaging accompanying each diagnosis. The overall prevalence of diagnosed spinal degenerative disease was 27.3% and increased with age. The prevalence of diagnosed disc disease was 2.7 times greater in those with radiology. The results demonstrate that degenerative findings in the spine are common, and, since asymptomatic individuals may not receive a diagnosis of degenerative conditions, this analysis likely underestimates the general prevalence of these conditions.

Human spinal balance assessment relies considerably on sagittal radiographic parameter measurement. Deep learning could be applied for automatic landmark detection and alignment analysis, with mild to moderate standard errors and favourable correlations with manual measurement. In this study, based on 2210 annotated images of various spinal disease aetiologies, we developed deep learning models capable of automatically locating 45 anatomic landmarks and subsequently generating 18 radiographic parameters on a whole-spine lateral radiograph. In the assessment of model performance, the localisation accuracy and learning speed were the highest for landmarks in the cervical area, followed by those in the lumbosacral, thoracic, and femoral areas. All the predicted radiographic parameters were significantly correlated with ground truth values (all p  < 0.001). The human and artificial intelligence comparison revealed that the deep learning model was capable of matching the reliability of doctors for 15/18 of the parameters. The proposed automatic alignment analysis system was able to localise spinal anatomic landmarks with high accuracy and to generate various radiographic parameters with favourable correlations with manual measurements.

Bone marrow adipose tissue (BMAT) comprises >10% of total adipose mass, yet unlike white or brown adipose tissues (WAT or BAT) its metabolic functions remain unclear. Herein, we address this critical gap in knowledge. Our transcriptomic analyses revealed that BMAT is distinct from WAT and BAT, with altered glucose metabolism and decreased insulin responsiveness. We therefore tested these functions in mice and humans using positron emission tomography-computed tomography (PET/CT) with 18 F-fluorodeoxyglucose. This revealed that BMAT resists insulin- and cold-stimulated glucose uptake, while further in vivo studies showed that, compared to WAT, BMAT resists insulin-stimulated Akt phosphorylation. Thus, BMAT is functionally distinct from WAT and BAT. However, in humans basal glucose uptake in BMAT is greater than in axial bones or subcutaneous WAT and can be greater than that in skeletal muscle, underscoring the potential of BMAT to influence systemic glucose homeostasis. These PET/CT studies characterise BMAT function in vivo, establish new methods for BMAT analysis, and identify BMAT as a distinct, major adipose tissue subtype. Bone marrow adipose tissue (BMAT) comprises over 10% of total fat mass but its systemic metabolic role is unclear. Here, the authors show that BMAT glucose uptake is not insulin or cold responsive; however, BMAT basal glucose uptake is higher than in white adipose tissue or skeletal muscle, underscoring BMAT’s potential to influence systemic glucose homeostasis.

Osteocytes are master regulators of the skeleton. We mapped the transcriptome of osteocytes from different skeletal sites, across age and sexes in mice to reveal genes and molecular programs that control this complex cellular-network. We define an osteocyte transcriptome signature of 1239 genes that distinguishes osteocytes from other cells. 77% have no previously known role in the skeleton and are enriched for genes regulating neuronal network formation, suggesting this programme is important in osteocyte communication. We evaluated 19 skeletal parameters in 733 knockout mouse lines and reveal 26 osteocyte transcriptome signature genes that control bone structure and function. We showed osteocyte transcriptome signature genes are enriched for human orthologs that cause monogenic skeletal disorders ( P  = 2.4 × 10 −22 ) and are associated with the polygenic diseases osteoporosis ( P  = 1.8 × 10 −13 ) and osteoarthritis ( P  = 1.6 × 10 −7 ). Thus, we reveal the molecular landscape that regulates osteocyte network formation and function and establish the importance of osteocytes in human skeletal disease. Osteocytes are the master regulatory cells within the skeleton. Here, the authors map the transcriptome of osteocytes from diverse skeletal sites, ages and between sexes and identify an osteocyte transcriptome signature associated with rare skeletal disorders and common complex skeletal diseases.

Recent interest in the control of bone metabolism has focused on a specialized subset of CD31 hi endomucin hi vessels, which are reported to couple angiogenesis with osteogenesis. However, the underlying mechanisms that link these processes together remain largely undefined. Here we show that the zinc-finger transcription factor ZEB1 is predominantly expressed in CD31 hi endomucin hi endothelium in human and mouse bone. Endothelial cell-specific deletion of ZEB1 in mice impairs CD31 hi endomucin hi vessel formation in the bone, resulting in reduced osteogenesis. Mechanistically, ZEB1 deletion reduces histone acetylation on Dll 4 and Notch1 promoters, thereby epigenetically suppressing Notch signaling, a critical pathway that controls bone angiogenesis and osteogenesis. ZEB1 expression in skeletal endothelium declines in osteoporotic mice and humans. Administration of Zeb1 -packaged liposomes in osteoporotic mice restores impaired Notch activity in skeletal endothelium, thereby promoting angiogenesis-dependent osteogenesis and ameliorating bone loss. Pharmacological reversal of the low ZEB1/Notch signaling may exert therapeutic benefit in osteoporotic patients by promoting angiogenesis-dependent bone formation. An endothelial cell subtype, expressing endomucin and CD31, has been reported to couple angiogenesis with osteogenesis. Here, the authors show that loss of ZEB1 in these cells epigenetically suppresses Notch signaling, leading to impaired angiogenesis and osteogenesis, and that Zeb1 delivery via liposomes ameliorates bone loss in osteoporotic mice

Skeletal stem cells (SSCs) and related progenitors with osteogenic potential, collectively termed skeletal stem and/or progenitor cells (SSPCs), are crucial for providing osteoblasts for bone formation during homeostatic tissue turnover and fracture repair. Besides mediating normal bone physiology, they also have important roles in various metabolic bone diseases, including osteoporosis. SSPCs are of tremendous interest because they represent prime future targets for osteoanabolic therapies and bone regenerative medicine. Remarkable progress has been made in characterizing various SSC and SSPC populations in postnatal bone. SSPCs exist in the periosteum and within the bone marrow stroma, including subsets localizing around arteriolar and sinusoidal blood vessels; they can display osteogenic, chondrogenic, adipogenic and/or fibroblastic potential, and exert critical haematopoiesis-supportive functions. However, much remains to be clarified. By the current markers, bona fide SSCs are commonly contained within broader SSPC populations characterized by considerable heterogeneity and overlap, whose common versus specific functions in health and disease have not been fully unravelled. Here, we review the present knowledge of the identity, fates and relationships of SSPC populations in the postnatal bone environment, their contributions to bone maintenance, the changes observed upon ageing, and the effect of metabolic diseases such as osteoporosis and diabetes mellitus. Various populations of skeletal stem and progenitor cells (SSPCs) exist within the native skeletal environments of humans and mice, with complex roles in the maintenance of bone tissue. This Review discusses the current state of knowledge of the identity and roles of SSPCs in skeletal health, disease and ageing. Key points Skeletal stem and/or progenitor cells (SSPCs) have crucial roles in bone physiology by giving rise to osteoblasts, chondrocytes and adipocytes, regulating osteoclastogenesis and angiogenesis and providing haematopoiesis-supportive stromal cells. Pure populations of skeletal stem cells (SSCs) are challenging to identify; by the currently available cell surface and genetic markers, bona fide SSCs are usually contained within broader SSPC populations and lineages. Ageing affects SSPCs cell-autonomously and by disrupting their niches, and is linked to reduced availability and adipogenesis-biased differentiation of SSPCs, cellular senescence, loss of bone mass, vascular decline and inflammageing. SSPCs are involved in various metabolic and endocrine bone diseases, including postmenopausal osteoporosis, diabetic bone disease, glucocorticoid-induced osteoporosis, and probably many others, but their precise roles require further clarification. Further in-depth characterization of the identity and regulatory control of SSPCs, particularly human SSPCs, is needed to explore and utilize the full therapeutic potential of these cells. Advances in single-cell multiomics, 3D-imaging technologies and genetic systems provide powerful tools for untangling heterogeneity and increasing insights into the specific markers, localization, relationships and function of mouse and human SSPC populations in health and disease.

Despite the relative ease of locating organs in the human body, automated organ segmentation has been hindered by the scarcity of labeled training data. Due to the tedium of labeling organ boundaries, most datasets are limited to either a small number of cases or a single organ. Furthermore, many are restricted to specific imaging conditions unrepresentative of clinical practice. To address this need, we developed a diverse dataset of 140 CT scans containing six organ classes: liver, lungs, bladder, kidney, bones and brain. For the lungs and bones, we expedited annotation using unsupervised morphological segmentation algorithms, which were accelerated by 3D Fourier transforms. Demonstrating the utility of the data, we trained a deep neural network which requires only 4.3 s to simultaneously segment all the organs in a case. We also show how to efficiently augment the data to improve model generalization, providing a GPU library for doing so. We hope this dataset and code, available through TCIA, will be useful for training and evaluating organ segmentation models. Measurement(s) organ subunit • image segmentation • brain segmentation • anatomical phenotype annotation Technology Type(s) unsupervised machine learning • Manual • computed tomography • supervised machine learning Factor Type(s) human organ Sample Characteristic - Organism Homo sapiens Machine-accessible metadata file describing the reported data: https://doi.org/10.6084/m9.figshare.13055663

Key Points The pathogenesis of primary osteoporosis is complex and influenced by both environmental and genetic factors Oxidative stress, apoptosis, sex-steroid deficiency and macroautophagy are age-related risk factors that contribute to the pathogenesis of osteoporosis Lifestyle-related factors, such as inadequate intake of calcium and vitamin D, physical inactivity, smoking and excessive alcohol consumption are important risk factors for osteoporosis Mutations in several genes can cause different monogenic disorders characterized by decreased bone mineral density and increased bone fragility The contribution of genetic factors to polygenic osteoporosis is determined by the presence of variants in many genes, each with a small effect size This article discusses the many heritable and nonheritable factors contributing to primary osteoporosis, focusing on osteogenesis imperfecta, juvenile osteoporosis and other monogenic disorders associated with increased bone fragility. Understanding these conditions not only illuminates the pathogenesis of osteoporosis, but could also lead to the discovery of new therapeutic targets. Osteoporosis is a common disorder, affecting hundreds of millions of people worldwide, and characterized by decreased bone mineral density and increased fracture risk. Known nonheritable risk factors for primary osteoporosis include advanced age, sex-steroid deficiency and increased oxidative stress. Age is a nonmodifiable risk factor, but the influence of a person's lifestyle (diet and physical activity) on their bone structure and density is modifiable to some extent. Heritable factors influencing bone fragility can be monogenic or polygenic. Osteogenesis imperfecta, juvenile osteoporosis and syndromes of decreased bone density are discussed as examples of monogenic disorders associated with bone fragility. So far, the factors associated with polygenic osteoporosis have been investigated mainly in genome-wide association studies. However, epigenetic mechanisms also contribute to the heritability of polygenic osteoporosis. Identification of these heritable and nonheritable risk factors has already led to the discovery of therapeutic targets for osteoporosis, which emphasizes the importance of research into the pathogenetic mechanisms of osteoporosis. Accordingly, this article discusses the many heritable and nonheritable factors that contribute to the pathogenesis of primary osteoporosis. Although osteoporosis can also develop secondary to many other diseases or their treatment, a discussion of the factors that contribute only to secondary osteoporosis is beyond the scope of this Review.

Squamates (lizards and snakes) include more than 10,000 living species, descended from an ancestor that diverged more than 240 million years ago from that of their closest living relative, Sphenodon . However, a deficiency of fossil evidence 1 – 7 , combined with serious conflicts between molecular and morphological accounts of squamate phylogeny 8 – 13 (but see ref.  14 ), has caused uncertainty about the origins and evolutionary assembly of squamate anatomy. Here we report the near-complete skeleton of a stem squamate, Bellairsia gracilis , from the Middle Jurassic epoch of Scotland, documented using high-resolution synchrotron phase-contrast tomography. Bellairsia shares numerous features of the crown group, including traits related to cranial kinesis (an important functional feature of many extant squamates) and those of the braincase and shoulder girdle. Alongside these derived traits, Bellairsia also retains inferred ancestral features including a pterygoid–vomer contact and the presence of both cervical and dorsal intercentra. Phylogenetic analyses return strong support for Bellairsia as a stem squamate, suggesting that several features that it shares with extant gekkotans are plesiomorphies, consistent with the molecular phylogenetic hypothesis that gekkotans are early-diverging squamates. We also provide confident support of stem squamate affinities for the enigmatic Oculudentavis . Our findings indicate that squamate-like functional features of the suspensorium, braincase and shoulder girdle preceded the origin of their palatal and vertebral traits and indicate the presence of advanced stem squamates as persistent components of terrestrial assemblages up to at least the middle of the Cretaceous period. A study using high-resolution synchrotron phase-contrast tomography documents the near-complete skeleton of a stem squamate, Bellairsia gracilis , from the Middle Jurassic epoch of Scotland, providing insights into early squamate anatomy.

Millions of skeletal remains from South Asia were exported in red markets (the underground economy of human tissues/organs) to educational institutions globally for over a century. It is time to recognize the personhood of the people who were systematically made into anatomical objects and acknowledge the scientific racism in creating and continuing to use them.