Bone augmentation with alloplastic graft material in a patient under bisphosphonate therapy: A case report and literature review.

Cases of relatively safe dental implant treatment in patients with low-volume bisphosphonate (BP) have been gradually reported. Although bone augmentation is commonly used when the bone volume is insufficient for implant placement, the studies and case reports regarding the safety of bone augmentation in patients treated with BP remain insufficient. Herein, we report a case wherein bone augmentation was performed after BP treatment, with bone healing realized according to imaging, and we review the literature regarding BP and bone augmentation. A sixty-seven-year-old Japanese woman requested implant treatment for a hopeless lower right second molar. She had been taking minodronic acid hydrate (50 mg/4 wk) for 18 mo to treat steroid-induced osteoporosis. After obtaining informed consent, tooth extraction and bone augmentation within the extraction socket were performed. The tooth was extracted atraumatically to preserve the surrounding alveolar bone, and the extraction socket was intensely curetted. Subsequently, the socket was filled with carbonate apatite granules and covered with a biodegradable membrane, and the wound was sutured without tension. Although protracted wound healing without any symptoms of infection was observed, the wound healed completely. No clinical symptoms were observed, the color of the mucosa at the site was healthy, and imaging findings at a six month post-operation indicated that osteogenesis had progressed uneventfully.

Role of signaling pathways in age-related orthopedic diseases: focus on the fibroblast growth factor family.

Fibroblast growth factor (FGF) signaling encompasses a multitude of functions, including regulation of cell proliferation, differentiation, morphogenesis, and patterning. FGFs and their receptors (FGFR) are crucial for adult tissue repair processes. Aberrant FGF signal transduction is associated with various pathological conditions such as cartilage damage, bone loss, muscle reduction, and other core pathological changes observed in orthopedic degenerative diseases like osteoarthritis (OA), intervertebral disc degeneration (IVDD), osteoporosis (OP), and sarcopenia. In OA and IVDD pathologies specifically, FGF1, FGF2, FGF8, FGF9, FGF18, FGF21, and FGF23 regulate the synthesis, catabolism, and ossification of cartilage tissue. Additionally, the dysregulation of FGFR expression (FGFR1 and FGFR3) promotes the pathological process of cartilage degradation. In OP and sarcopenia, endocrine-derived FGFs (FGF19, FGF21, and FGF23) modulate bone mineral synthesis and decomposition as well as muscle tissues. FGF2 and other FGFs also exert regulatory roles. A growing body of research has focused on understanding the implications of FGF signaling in orthopedic degeneration. Moreover, an increasing number of potential targets within the FGF signaling have been identified, such as FGF9, FGF18, and FGF23. However, it should be noted that most of these discoveries are still in the experimental stage, and further studies are needed before clinical application can be considered. Presently, this review aims to document the association between the FGF signaling pathway and the development and progression of orthopedic diseases. Besides, current therapeutic strategies targeting the FGF signaling pathway to prevent and treat orthopedic degeneration will be evaluated.

Vertebral HU value and the pectoral muscle index based on chest CT can be used to opportunistically screen for osteoporosis.

BACKGROUND: Existing studies have shown that computed tomography (CT) attenuation and skeletal muscle tissue are strongly associated with osteoporosis; however, few studies have examined whether vertebral HU values and the pectoral muscle index (PMI) measured at the level of the 4th thoracic vertebra (T4) are strongly associated with bone mineral density (BMD). In this study, we demonstrate that vertebral HU values and the PMI based on chest CT can be used to opportunistically screen for osteoporosis and reduce fracture risk through prompt treatment. METHODS: We retrospectively evaluated 1000 patients who underwent chest CT and DXA scans from August 2020-2022. The T4 HU value and PMI were obtained using manual chest CT measurements. The participants were classified into normal, osteopenia, and osteoporosis groups based on the results of dual-energy X-ray (DXA) absorptiometry. We compared the clinical baseline data, T4 HU value, and PMI between the three groups of patients and analyzed the correlation between the T4 HU value, PMI, and BMD to further evaluate the diagnostic efficacy of the T4 HU value and PMI for patients with low BMD and osteoporosis. RESULTS: The study ultimately enrolled 469 participants. The T4 HU value and PMI had a high screening capacity for both low BMD and osteoporosis. The combined diagnostic model-incorporating sex, age, BMI, T4 HU value, and PMI-demonstrated the best diagnostic efficacy, with areas under the receiver operating characteristic curve (AUC) of 0.887 and 0.892 for identifying low BMD and osteoporosis, respectively. CONCLUSIONS: The measurement of T4 HU value and PMI on chest CT can be used as an opportunistic screening tool for osteoporosis with excellent diagnostic efficacy. This approach allows the early prevention of osteoporotic fractures via the timely screening of individuals at high risk of osteoporosis without requiring additional radiation.

Exploring the interplay between paraspinal muscular status and bone health in osteoporosis and fracture risk: a comprehensive literature review on computed tomography (CT) and magnetic resonance imaging (MRI) studies.

Background and Objective: Computed tomography (CT) and magnetic resonance imaging (MRI) of the spine are fundamental non-invasive tools to investigate the status of the bone and soft tissue in vivo. A novel and promising approach is to investigate the quality and quantity of paraspinal muscles even beyond the clinical question. The aim of the present review is to summarize current evidence on CT and MRI about the relationship between paraspinal muscular status and bone health in osteoporosis (OP) and fracture risk. Methods: Literature research was carried out on September 2023 using PubMed, Scopus, and Cochrane databases. Key Content and Findings: Research investigating the intricate interplay between musculature and bone health reveals that degenerating paraspinal muscles, characterized by shrinking and fatty infiltration, are associated with lower bone mineral density (BMD) and the development of OP. Additionally, research indicates that weaker paraspinal muscles are linked to a higher risk of fractures, including those at the spine. Conclusions: The findings suggest that paraspinal muscle health may be a significant factor in identifying individuals at risk for OP and fractures. Further investigation is needed to explore the potential of paraspinal muscles in preventing these conditions.

Unveiling the unexplored novel signatures for osteoporosis via a detailed bioinformatics and molecular experiments based approach.

BACKGROUND: Osteoporosis (OP) stands as a prevalent bone ailment affecting the elderly, globally. The identification of reliable diagnostic markers crucially aids OP clinical management. METHODS: Utilizing the GEO database (GSE35959), we acquired expression profiles for OP and normal samples. Differential expression genes (DEGs) and hub genes were pinpointed through STRING, GEO2R, and Cytoscape. The competing endogenous RNA (ceRNA) network was constructed using miRTarBase, miRDB, and MiRcode databases. Gene Ontology (GO) and KEGG pathway enrichment analyses were performed via DAVID. Validation involved clinical OP samples from the Pakistani population, with Real-Time Quantitative Polymerase Chain Reaction (RT-qPCR) assessing hub gene expression. RESULTS: A total of 2124 differentially expressed genes (DEGs) were identified between OP and normal samples in GSE35959. The selected hub genes among these DEGs were Splicing Factor 3a Subunit 1 (SF3A1), Ataxin 2 Like (ATXN2L), Heat Shock Protein 90 Beta Family Member 1 (HSP90B1), Cluster of Differentiation 74 (CD74), DExH-Box Helicase 29 (DHX29), ALG5 Dolichyl-Phosphate Beta-Glucosyltransferase (ALG5), NudC Domain Containing 2 (NUDCD2), and Ras-related protein Rab-2A (RAB2A). Expression validation of these genes on the Pakistani OP patients revealed significant up-regulation of SF3A1, ATXN2L, and CD74 and significant (P < 0.05) down-regulation of HSP90B1, DHX29, ALG5, NUDCD2, and RAB2A in OP patients. Receiver operating characteristic (ROC) analysis demonstrated that these hub genes displayed considerable diagnostic accuracy for detecting OP. The ceRNA network analysis of the hub genes revealed some important hub genes' regulatory miRNAs and lncRNAs. Via KEGG analysis, hub genes were found to be enriched in N-Glycan biosynthesis, Thyroid hormone synthesis, IL-17 signaling pathway, Prostate cancer, AMPK signaling pathway, Spliceosome, Estrogen signaling pathway, and Fluid shear stress and atherosclerosis, etc., pathways. CONCLUSION: The identified eight hub genes in the present study could reliably distinguish OP patients from normal individuals, which may provide novel insight into the diagnostic research of OP.

Integration of bioinformatics and machine learning approaches for the validation of pyrimidine metabolism-related genes and their implications in immunotherapy for osteoporosis.

BACKGROUND: Osteoporosis (OP), the "silent epidemic" of our century, poses a significant challenge to public health, predominantly affecting postmenopausal women and the elderly. It evolves from mild symptoms to pronounced severity, stabilizing eventually. Unique among OP's characteristics is the altered metabolic profile of affected cells, particularly in pyrimidine metabolism (PyM), a crucial pathway for nucleotide turnover and pyrimidine decomposition. While metabolic adaptation is acknowledged as a therapeutic target in various diseases, the specific role of PyM genes (PyMGs) in OP's molecular response remains to be clarified. METHODS: In pursuit of elucidating and authenticating PyMGs relevant to OP, we embarked on a comprehensive bioinformatics exploration. This entailed the integration of Weighted Gene Co-expression Network Analysis (WGCNA) with a curated list of 37 candidate PyMGs, followed by the examination of their biological functions and pathways via Gene Set Variation Analysis (GSVA). The Least Absolute Shrinkage and Selection Operator (LASSO) technique was harnessed to identify crucial hub genes. We evaluated the diagnostic prowess of five PyMGs in OP detection and explored their correlation with OP's clinical traits, further validating their expression profiles through independent datasets (GSE2208, GSE7158, GSE56815, and GSE35956). RESULTS: Our analytical rigor unveiled five PyMGs-IGKC, TMEM187, RPS11, IGLL3P, and GOLGA8N-with significant ties to OP. A deeper dive into their biological functions highlighted their roles in estrogen response modulation, cytosolic calcium ion concentration regulation, and GABAergic synaptic transmission. Remarkably, these PyMGs emerged as potent diagnostic biomarkers for OP, distinguishing affected individuals with substantial accuracy. CONCLUSIONS: This investigation brings to light five PyMGs intricately associated with OP, heralding new avenues for biomarker discovery and providing insights into its pathophysiological underpinnings. These findings not only deepen our comprehension of OP's complexity but also herald the advent of more refined diagnostic and therapeutic modalities.

Gut microbially produced tryptophan metabolite melatonin ameliorates osteoporosis via modulating SCFA and TMAO metabolism.

Osteoporosis (OP) is a severe global health issue that has significant implications for productivity and human lifespan. Gut microbiota dysbiosis has been demonstrated to be closely associated with OP progression. Melatonin (MLT) is an important endogenous hormone that modulates bone metabolism, maintains bone homeostasis, and improves OP progression. Multiple studies indicated that MLT participates in the regulation of intestinal microbiota and gut barrier function. However, the promising effects of gut microbiota-derived MLT in OP remain unclear. Here, we found that OP resulted in intestinal tryptophan disorder and decreased the production of gut microbiota-derived MLT, while administration with MLT could mitigate OP-related clinical symptoms and reverse gut microbiota dysbiosis, including the diversity of intestinal microbiota, the relative abundance of many probiotics such as Allobaculum and Parasutterella, and metabolic function of intestinal flora such as amino acid metabolism, nucleotide metabolism, and energy metabolism. Notably, MLT significantly increased the production of short-chain fatty acids and decreased trimethylamine N-oxide-related metabolites. Importantly, MLT could modulate the dynamic balance of M1/M2 macrophages, reduce the serum levels of pro-inflammatory cytokines, and restore gut-barrier function. Taken together, our results highlighted the important roles of gut microbially derived MLT in OP progression via the "gut-bone" axis associated with SCFA metabolism, which may provide novel insight into the development of MLT as a promising drug for treating OP.

Bone Health Impairment in Patients with Hemoglobinopathies: From Biological Bases to New Possible Therapeutic Strategies.

Hemoglobinopathies are monogenic disorders affecting hemoglobin synthesis. Thalassemia and sickle cell disease (SCD) are considered the two major hemoglobinopathies. Thalassemia is a genetic disorder and one of the major hemoglobinopathies determined by an impairment of globin chain production, which causes an alteration of erythropoiesis, an improvement in hemolysis, and an alteration of iron homoeostasis. In SCD, the mutations are on the ß-globin chain of hemoglobin which results in a substitution of glutamic acid by valine with consequent formation of Hemoglobin S (HbS). Several factors are involved in bone metabolism alteration in patients with hemoglobinopathies, among them hormonal deficiency, bone marrow hyperplasia, iron overload, inflammation, and increased bone turnover. Bone metabolism is the result of balance maintenance between bone deposition and bone resorption, by osteoblasts (OBs) and osteoclasts (OCs). An impairment of this balance is responsible for the onset of bone diseases, such as osteoporosis (OP). Therefore, here we will discuss the alteration of bone metabolism in patients with hemoglobinopathies and the possible therapeutic strategies to contain and/or counteract bone health impairment in these patients, taking into consideration not only the pharmacological treatments already used in the clinical armamentarium, but also the new possible therapeutic strategies.

Rheumatoid Arthritis Patient With Neurofibromatosis Type 1: Case Report and Review of the Literature.

A 66-year-old neurofibromatosis type 1 (NF1) patient with polyarticular pain for nine years, aggravated for two days, was transferred from the Emergency Intensive Care Unit (EICU) to our rheumatology department. She was diagnosed with NF1 nine years ago by a gene mutation detection and coronary heart disease (CHD) three months ago. The patient was diagnosed with rheumatoid arthritis (RA) this time. After 24 days of treatment with appropriate medication, the patient was discharged with relieved joint pain. However, about four months later, the patient died of circulatory failure caused by myocardial infarction. We analyzed the possible reasons for her outcome and made a review of the literature. There are few clinical reports of NF1 complicated with RA. We found five cases reported in the literature up to date during our search and included them in our communication to compare with our case. NF1 combined with RA mainly affects adult women and usually starts with NF1 and is followed by RA after at least six years of NF1 symptom onset. Although the summarized characteristics of clinical and potential pathogenesis of NF1 combined with RA were limited with these six cases, we hope that this will help clinicians to increase their understanding of this rare complication, thus helping to guide clinical medication.

Identifying Crucial Biomarkers in Osteoporosis and Ulcerative Colitis Through Bioinformatics Analysis of Co-expressed Genes.

Osteoporosis (OP) and ulcerative colitis (UC), prevalent immune diseases, exert a substantial socioeconomic impact globally. This study identifies biomarkers for these diseases, paving the way for in-depth research. Initially, the Gene Expression Omnibus (GEO) database was employed to analyze datasets GSE35958 and GSE87466. This analysis aimed to pinpoint co-expression differential genes (DEGs) between OP and UC. Subsequently, the Metascape database facilitated the Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis of these DEGs' co-expression. For network construction and visualization, the STRING11.5 database along with Cytoscape 3.7.2 (Cytoscape Team, USA) were utilized to create a protein-protein interaction (PPI) network. Moreover, Cytoscape's cytoHubba plugin was instrumental in identifying the central genes, known as hub genes. In the datasets GSE35958 and GSE87466, 156 co-expressed DEGs were discovered. The PPI network, constructed using STRING11.5 and Cytoscape 3.7.2, comprises 96 nodes and 222 connections. Notably, seven hub genes were identified, namely COL6A1, COL6A2, BGN, NID1, PLAU, TGFB1, and PLAUR. These DEGs were predominantly enriched in pathways such as extracellular matrix organization and collagen-containing extracellular matrix, as per GO analysis. For diagnostic model construction and hub gene validation, datasets GSE56815 and GSE107499 from the GEO database were employed. The top five hub genes were validated. In conclusion, the hub genes identified in this study played a significant role in the early diagnosis, prevention, and treatment of OP and UC. Furthermore, they provide fresh insights into the underlying mechanisms of these diseases' development and progression.

Bioinformatics and machine learning were used to validate glutamine metabolism-related genes and immunotherapy in osteoporosis patients.

BACKGROUND: Osteoporosis (OP), often referred to as the "silent disease of the twenty-first century," poses a significant public health concern due to its severity, chronic nature, and progressive course, predominantly affecting postmenopausal women and elderly individuals. The pathogenesis and progression of this disease have been associated with dysregulation in tumor metabolic pathways. Notably, the metabolic utilization of glutamine has emerged as a critical player in cancer biology. While metabolic reprogramming has been extensively studied in various malignancies and linked to clinical outcomes, its comprehensive investigation within the context of OP remains lacking. METHODS: This study aimed to identify and validate potential glutamine metabolism genes (GlnMgs) associated with OP through comprehensive bioinformatics analysis. The identification of GlnMgs was achieved by integrating the weighted gene co-expression network analysis and a set of 28 candidate GlnMgs. Subsequently, the putative biological functions and pathways associated with GlnMgs were elucidated using gene set variation analysis. The LASSO method was employed to identify key hub genes, and the diagnostic efficacy of five selected GlnMgs in OP detection was assessed. Additionally, the relationship between hub GlnMgs and clinical characteristics was investigated. Finally, the expression levels of the five GlnMgs were validated using independent datasets (GSE2208, GSE7158, GSE56815, and GSE35956). RESULTS: Five GlnMgs, namely IGKC, TMEM187, RPS11, IGLL3P, and GOLGA8N, were identified in this study. To gain insights into their biological functions, particular emphasis was placed on synaptic transmission GABAergic, inward rectifier potassium channel activity, and the cytoplasmic side of the lysosomal membrane. Furthermore, the diagnostic potential of these five GlnMgs in distinguishing individuals with OP yielded promising results, indicating their efficacy as discriminative markers for OP. CONCLUSIONS: This study discovered five GlnMgs that are linked to OP. They shed light on potential new biomarkers for OP and tracking its progression.

Modulation of SIRT6 activity acts as an emerging therapeutic implication for pathological disorders in the skeletal system.

The skeletal system is a dynamically balanced system, which undergoes continuous bone resorption and formation to maintain bone matrix homeostasis. As an important ADP-ribosylase and NAD+-dependent deacylase, SIRT6 (SIR2-like protein 6) is widely expressed on various kinds of bone cells, such as chondrocytes, osteoblasts, osteoclasts. The aberration of SIRT6 impairs gene expression (e.g., NF-κB and Wnt target genes) and cellular functions (e.g., DNA repair, glucose and lipid metabolism, telomeric maintenance), which disturbs the dynamic balance and ultimately leads to several bone-related diseases. In this review, we summarize the critical roles of SIRT6 in the onset and progression of bone-related diseases including osteoporosis, osteoarthritis, rheumatoid arthritis, and intervertebral disc degeneration, as well as the relevant signaling pathways. In addition, we discuss the advances in the development of SIRT6 activators and elucidate their pharmacological profiles, which may provide novel treatment strategies for these skeletal diseases.

Engineered extracellular vesicles as therapeutics of degenerative orthopedic diseases.

Degenerative orthopedic diseases, as a global public health problem, have made serious negative impact on patients' quality of life and socio-economic burden. Traditional treatments, including chemical drugs and surgical treatments, have obvious side effects and unsatisfactory efficacy. Therefore, biological therapy has become the focus of researches on degenerative orthopedic diseases. Extracellular vesicles (EVs), with superior properties of immunoregulatory, growth support, and drug delivery capabilities, have emerged as a new cell-free strategy for the treatment of many diseases, including degenerative orthopedic diseases. An increasing number of studies have shown that EVs can be engineered through cargo loading, surface modification, and chemical synthesis to improve efficiency, specificity, and safety. Herein, a comprehensive overview of recent advances in engineering strategies and applications of engineered EVs as well as related researches in degenerative orthopedic diseases, including osteoarthritis (OA), osteoporosis (OP), intervertebral disc degeneration (IDD) and osteonecrosis of the femoral head (ONFH), is provided. In addition, we analyze the potential and challenges of applying engineered EVs to clinical practice.

Does Lumbar Interbody Fusion Modality Affect the Occurrence of Complications in an Osteoporotic Spine Under Whole-Body Vibration? A Finite Element Study.

OBJECTIVE: To evaluate the effects of 3 lumbar interbody fusion techniques on the occurrence of complications in an osteoporotic spine under whole-body vibration. METHODS: A previously developed and validated nonlinear finite element model of L1-S1was modified to develop anterior lumbar interbody fusion (ALIF), posterior lumbar interbody fusion (PLIF), and transforaminal lumbar interbody fusion (TLIF) models with osteoporosis. In each model, the lower surface of the sacrum was absolutely fixed, a follower load of 400N was applied through the axis of the lumbar spine, and an axial sinusoidal vertical load of ±40N (5 Hz) was imposed on the superior surface of L1, to perform a transient dynamic analysis. The maximal values of intradiscal pressure, shear stress on annulus substance, disc bulge, facet joint stress, and screw and rod stress, along with their dynamic response curves, were collected. RESULTS: Among these 3 models, the TLIF model generated the greatest screw and rod stress, and the PLIF model generated the greatest cage-bone interface stress. At the L3-L4 level, compared with the other 2 models, the maximal values and dynamic response curves of intradiscal pressure, shear stress of annulus ground substance, and disc bulge were all lower in the ALIF model. However, the facet contact stress at the adjacent segment in the ALIF model was higher than that in the other 2 models. CONCLUSIONS: In an osteoporotic spine under whole-body vibration, TLIF has the highest risk of screw and rod breakage, PLIF has the highest risk of cage subsidence, and ALIF has the lowest risk of upper adjacent disc degeneration, but the highest risk of adjacent facet joint degeneration.

Gold-nanosphere mitigates osteoporosis through regulating TMAO metabolism in a gut microbiota-dependent manner.

Osteoporosis (OP) is a metabolic bone disease characterized by decreased bone mass and increased bone fragility. The imbalance of bone homeostasis modulated by osteoclasts and osteoblasts is the most crucial pathological change in osteoporosis. As a novel treatment strategy, nanomedicine has been applied in drug delivery and targeted therapy due to its high efficiency, precision, and fewer side effects. Gold nanospheres (GNS), as a common kind of gold nanoparticles (GNPs), possess significant antimicrobial and anti-inflammatory activity, which have been applied for the treatment of eye diseases and rheumatoid arthritis. However, the effect of GNS on osteoporosis remains elusive. In this study, we found that GNS significantly prevented ovariectomy (OVX)-induced osteoporosis in a gut microbiota-dependent manner. 16S rDNA gene sequencing demonstrated GNS markedly altered the gut microbial diversity and flora composition. In addition, GNS reduced the abundance of TMAO-related metabolites in OVX mice. Low TMAO levels might alleviate the bone loss phenomenon by reducing the inflammation response. Therefore, we investigated the alteration of cytokine profiles in OVX mice. GNS inhibited the release of pro-osteoclastogenic or proinflammatory cytokines including tumor necrosis factor α (TNF-α), interleukin (IL)-6, and granulocyte colony-stimulating factor (G-CSF) in the serum. In conclusion, GNS suppressed estrogen deficiency-induced bone loss by regulating the destroyed homeostasis of gut microbiota so as to reduce its relevant TMAO metabolism and restrain the release of proinflammatory cytokines. These results demonstrated the protective effects of GNS on osteoporosis as a gut microbiota modulator and offered novel insights into the regulation of the "gut-bone" axis.

Application of intelligent X-ray image analysis in risk assessment of osteoporotic fracture of femoral neck in the elderly.

The paper focuses on establishing a risk assessment model of femoral neck osteoporotic fracture (FNOF) in the elderly population and improving the screening efficiency and accuracy of such diseases in specific populations. In literature research, the main risk factors of femoral neck osteoporosis (FNOP) in the elderly were studied and analyzed; the femur region of interest (ROI) and the hard bone edge segmentation model were selected from the X-ray digital image by using the image depth learning method. On this basis, the femoral trabecular score and femoral neck strength (FNS) in the set region were selected as the main evaluation elements, and the quantitative analysis method was established; an X-ray image processing method was applied to the feasibility study of FNOP and compared with dual-energy X-ray absorptiometry measurements of bone mineral density; Finally, the main risk factors of FNOP were selected and the prediction model of FNOP in the elderly population was established based on medical image processing, machine learning model construction and other methods. Some FNOP health records were selected as test samples for comparative analysis with traditional manual evaluation methods. The paper shows the risk assessment model of FNOF in the elderly population, which is feasible in testing. Among them, the artificial neural network model had a better accuracy (95.83%) and recall rate (100.00%), and the support vector machine prediction model had high specificity (62.50%). With the help of a machine learning method to establish the risk assessment model of FNOF for the elderly, one can provide decision support for the fracture risk assessment of the elderly and remind the clinic to give targeted interventions for the above high-risk groups in order to reduce the fracture risk.

Machine learning applied to HR-pQCT images improves fracture discrimination provided by DXA and clinical risk factors.

BACKGROUND: Traditional analysis of High Resolution peripheral Quantitative Computed Tomography (HR-pQCT) images results in a multitude of cortical and trabecular parameters which would be potentially cumbersome to interpret for clinicians compared to user-friendly tools utilising clinical parameters. A computer vision approach (by which the entire scan is 'read' by a computer algorithm) to ascertain fracture risk, would be far simpler. We therefore investigated whether a computer vision and machine learning technique could improve upon selected clinical parameters in assessing fracture risk. METHODS: Participants of the Hertfordshire Cohort Study (HCS) attended research visits at which height and weight were measured; fracture history was determined via self-report and vertebral fracture assessment. Bone microarchitecture was assessed via HR-pQCT scans of the non-dominant distal tibia (Scanco XtremeCT), and bone mineral density measurement and lateral vertebral assessment were performed using dual-energy X-ray absorptiometry (DXA) (Lunar Prodigy Advanced). Images were cropped, pre-processed and texture analysis was performed using a three-dimensional local binary pattern method. These image data, together with age, sex, height, weight, BMI, dietary calcium and femoral neck BMD, were used in a random-forest classification algorithm. Receiver operating characteristic (ROC) analysis was used to compare fracture risk identification methods. RESULTS: Overall, 180 males and 165 females were included in this study with a mean age of approximately 76 years and 97 (28 %) participants had sustained a previous fracture. Using clinical risk factors alone resulted in an area under the curve (AUC) of 0.70 (95 % CI: 0.56-0.84), which improved to 0.71 (0.57-0.85) with the addition of DXA-measured BMD. The addition of HR-pQCT image data to the machine learning classifier with clinical risk factors and DXA-measured BMD as inputs led to an improved AUC of 0.90 (0.83-0.96) with a sensitivity of 0.83 and specificity of 0.74. CONCLUSION: These results suggest that using a three-dimensional computer vision method to HR-pQCT scanning may enhance the identification of those at risk of fracture beyond that afforded by clinical risk factors and DXA-measured BMD. This approach has the potential to make the information offered by HR-pQCT more accessible (and therefore) applicable to healthcare professionals in the clinic if the technology becomes more widely available.

Drug discovery in spinal cord injury-induced osteoporosis: a text mining-based study.

Background: Spinal cord injury (SCI) and osteoporosis (OP) are common diseases in spine surgery, and OP could be the complication of SCI. However, SCI-induced OP is a complex pathologic process and drug discovery is limited, which restricts the study in the mechanism and treatment of the disease. This study aims to identify the genes and molecular pathways related to SCI-induced OP through computational tools and public datasets, and to explore drug targeting therapy, ultimately preventing the occurrence of OP after SCI. Methods: In this study, common genes related to SCI and OP were obtained by text mining, then which conducted the functional analysis. Protein-protein interaction (PPI) networks were constructed by STRING online and Cytoscape software. Finally, core genes and potential drugs were performed after undergoing drug-gene interaction analysis which also completed functional analysis. Results: A total of 371 genes common to 'SCI' and 'OP' were identified by text mining. After functional analysis, 207 significant genes were screened out. Subsequently, PPI analysis yielded 23 genes targetable by 13 drugs which were the candidate to treat SCI-induced OP. Conclusions: Taken together, siltuximab, olokizumab, clazakizumab and BAN2401 were first discovered to become the potential drugs for the treatment of SCI-induced OP. Drug discovery using text mining and pathway analysis is a significant way to investigate the pathomechanism of the disease while exploring existing drugs to treat the disease.

16S rDNA analysis of osteoporotic rats treated with osteoking.

Introduction. Osteoporosis (OP) is characterized by microstructural degeneration of bone tissue, low bone mass, bone fragility and even brittle fracture (osteoporotic fracture, OPF). OP and OPF are common and there are many disadvantages to the current medications for OP/OPF. Osteoking is a traditional Chinese medicine (TCM) originating from the Yi nationality (Yunnan, China) that has been used to treat bone diseases for decades.Hypothesis/Gap Statement. This study will reveal the changes in the intestinal microbiota of OP rats after 70 days of osteoking treatment.Method. With duplication of sham and OP rats, eight groups were established, with six rats in each group. The intestinal microbiotas were analysed by 16S rDNA sequencing.Results. The results showed that osteoking changed the intestinal microbiota of sham rats and OP rats. The mechanism by which osteoking improves OP is related to the functions of the intestinal microbiota. After 70 days of treatment with osteoking, the contents of Pseudonocardia, Pedomicrobium, Variovorax, Niastella and Actinosynnema were decreased in OP rats. The functions of the above intestinal microbiota related to iron metabolism affected calcifediol and 25(OH)D, and measuring these bone metabolic indicators is required for further study.Conclusion. Osteoking changes the intestinal microbiota to improve OP, and further study which reveals these intestinal microbiota and mechanism is needed.

α-Asarone Attenuates Osteoclastogenesis and Prevents Against Oestrogen-Deficiency Induced Osteoporosis.

Osteoporosis (OP) is defined as low bone mineral density which features over activated osteoclasts (OCs) and bone resorption. Targeting excessive OCs activity is thought to be an effective therapeutic approach for OP treatment. α-asarone (ASA), a compound from the traditional Chinese medicinal herb Acorus tatarinowii, has been widely used as a therapeutic agent against several diseases such as epilepsy, cough, bronchitis and asthma for many years. Recently, it was reported that ASA-derived lignins which were purified from Acorus tatarinowii root tissues effectively suppressed both RANKL-induced osteoclastogenesis and bone resorption. Besides, a classic Chinese formulation Bajitianwan (BJTW) which consisted of root and rhizome of Acorus tatarinowii Schott also showed positive effects on age-related bone loss. In the present study, we aimed to study the effects of ASA on osteoclastogenesis in vitro and in vivo. As illustrated by TRAP staining, ASA was capable of inhibiting RANKL-induced osteoclastogenesis in a dose-dependent manner, not only at an early-stage, but also in the late-stage. Besides, it also effectively suppressed bone resorption of mature OCs in a pit resorption assay. The formation of F-actin ring during osteoclastogenesis, which was important in OCs bone-resorption, was impaired as well. Subsequent mechanism experiments exposed that ASA inhibited osteoclastogenesis related genes in a time-dependent manner through AKT, p38 and NF-κB, followed by NFATc1/c-fos signaling pathway. Notably, our in vivo study uncovered that ASA was capable of improving the bone microstructure in oestrogen-deficiency induced OP models. Thus, our current work highlighted the important role of an old drug ASA in bone metabolism especially in OCs differentiation. ASA may find its potential as a lead compound to treat excessive OCs activity-induced bone loss diseases and more structure optimization is further needed.