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.

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.

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.
CONCLUSIONS: 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.

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.

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.

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.

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.

To evaluate the effects of 3 lumbar interbody fusion techniques on the occurrence of complications in an osteoporotic spine under whole-body vibration.
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.
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.
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.

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.

UNASSIGNED: 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.
UNASSIGNED: 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.
UNASSIGNED: 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.
UNASSIGNED: 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.