Bone regeneration and repair are crucial to ambulation and quality of life. Factors such as poor general health, serious medical comorbidities, chronic inflammation, and ageing can lead to delayed healing and nonunion of fractures, and persistent bone defects. Bioengineering strategies to heal bone often involve grafting of autologous bone marrow aspirate concentrate (BMAC) or mesenchymal stem cells (MSCs) with biocompatible scaffolds. While BMAC shows promise, variability in its efficacy exists due to discrepancies in MSC concentration and robustness, and immune cell composition. Understanding the mechanisms by which macrophages and lymphocytes – the main cellular components in BMAC – interact with MSCs could suggest novel strategies to enhance bone healing. Macrophages are polarized into pro-inflammatory (M1) or anti-inflammatory (M2) phenotypes, and influence cell metabolism and tissue regeneration via the secretion of cytokines and other factors. T cells, especially helper T1 (Th1) and Th17, promote inflammation and osteoclastogenesis, whereas Th2 and regulatory T (Treg) cells have anti-inflammatory pro-reconstructive effects, thereby supporting osteogenesis. Crosstalk among macrophages, T cells, and MSCs affects the bone microenvironment and regulates the local immune response. Manipulating the proportion and interactions of these cells presents an opportunity to alter the local regenerative capacity of bone, which potentially could enhance clinical outcomes. Cite this article:
To investigate the effects of senescent osteocytes on bone homeostasis in the progress of age-related osteoporosis and explore the underlying mechanism. In a series of in vitro experiments, we used tert-Butyl hydroperoxide (TBHP) to induce senescence of MLO-Y4 cells successfully, and collected conditioned medium (CM) and senescent MLO-Y4 cell-derived exosomes, which were then applied to MC3T3-E1 cells, separately, to evaluate their effects on osteogenic differentiation. Furthermore, we identified differentially expressed microRNAs (miRNAs) between exosomes from senescent and normal MLO-Y4 cells by high-throughput RNA sequencing. Based on the key miRNAs that were discovered, the underlying mechanism by which senescent osteocytes regulate osteogenic differentiation was explored. Lastly, in the in vivo experiments, the effects of senescent MLO-Y4 cell-derived exosomes on age-related bone loss were evaluated in male SAMP6 mice, which excluded the effects of oestrogen, and the underlying mechanism was confirmed.Aims
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Aims. Astragalus polysaccharide (APS) participates in various processes, such as the enhancement of immunity and inhibition of tumours. APS can affect osteoporosis (OP) by regulating the osteogenic differentiation of human bone mesenchymal stem cells (hBMSCs). This study was designed to elucidate the mechanism of APS in hBMSC proliferation and osteoblast differentiation. Methods. Reverse transcriptase polymerase chain reaction (RT-PCR) and Western blotting were performed to determine the expression of
Aims. Long non-coding RNAs (lncRNAs) act as crucial regulators in osteoporosis (OP). Nonetheless, the effects and potential molecular mechanism of lncRNA PCBP1 Antisense RNA 1 (PCBP1-AS1) on OP remain largely unclear. The aim of this study was to explore the role of lncRNA PCBP1-AS1 in the pathogenesis of OP. Methods. Using quantitative real-time polymerase chain reaction (qRT-PCR), osteogenesis-related genes (alkaline phosphatase (ALP), osteocalcin (OCN), osteopontin (OPN), and Runt-related transcription factor 2 (RUNX2)), PCBP1-AS1,
We aimed to develop a gene signature that predicts the occurrence of postmenopausal osteoporosis (PMOP) by studying its genetic mechanism. Five datasets were obtained from the Gene Expression Omnibus database. Unsupervised consensus cluster analysis was used to determine new PMOP subtypes. To determine the central genes and the core modules related to PMOP, the weighted gene co-expression network analysis (WCGNA) was applied. Gene Ontology enrichment analysis was used to explore the biological processes underlying key genes. Logistic regression univariate analysis was used to screen for statistically significant variables. Two algorithms were used to select important PMOP-related genes. A logistic regression model was used to construct the PMOP-related gene profile. The receiver operating characteristic area under the curve, Harrell’s concordance index, a calibration chart, and decision curve analysis were used to characterize PMOP-related genes. Then, quantitative real-time polymerase chain reaction (qRT-PCR) was used to verify the expression of the PMOP-related genes in the gene signature.Aims
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Circular RNAs (circRNAs) are a novel type of non-coding RNA that plays major roles in the development of diverse diseases including osteonecrosis of the femoral head (ONFH). Here, we explored the impact of hsa_circ_0066523 derived from forkhead box P1 (FOXP1) (also called circFOXP1) on bone mesenchymal stem cells (BMSCs), which is important for ONFH development. RNA or protein expression in BMSCs was analyzed by quantitative real-time polymerase chain reaction (qRT-PCR) or western blot, respectively. Cell Counting Kit 8 (CCK8) and 5-ethynyl-2’-deoxyuridine (EdU) were used to analyze cell proliferation. Alkaline phosphatase (ALP) activity, ALP staining, and Alizarin Red S staining were employed to evaluate the osteoblastic differentiation. Chromatin immunoprecipitation (ChIP), luciferase reporter, RNA pull down, and RNA immunoprecipitation (RIP) assays were combined for exploring molecular associations.Aims
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Objectives. Diabetes mellitus (DM) is known to impair fracture healing. Increasing evidence suggests that some
