Osteoporosis (OP) is a chronic
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. 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, microRNA (miR)-126-5p, group I Pak family member p21-activated kinase 2 (PAK2), and their relative expression levels were determined. Western blotting was used to examine the expression of PAK2 protein. Cell Counting Kit-8 (CCK-8) assay was used to measure cell proliferation. To examine the osteogenic differentiation, Alizarin red along with ALP staining was used. RNA immunoprecipitation assay and bioinformatics analysis, as well as a dual-luciferase reporter, were used to study the association between PCBP1-AS1, PAK2, and miR-126-5p.Aims
Methods
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. Reverse transcriptase polymerase chain reaction (RT-PCR) and Western blotting were performed to determine the expression of microRNA (miR)-760 and ankyrin repeat and FYVE domain containing 1 (ANKFY1) in OP tissues and hBMSCs. Cell viability was measured using the Cell Counting Kit-8 assay. The expression of cyclin D1 and osteogenic marker genes (osteocalcin (OCN), alkaline phosphatase (ALP), and runt-related transcription factor 2 (RUNX2)) was evaluated using quantitative reverse transcriptase polymerase chain reaction (qRT-PCR). Mineral deposits were detected through Alizarin Red S staining. In addition, Western blotting was performed to detect the ANKFY1 protein levels following the regulation of miR-760. The relationship between miR-760 and ANKFY1 was determined using a luciferase reporter assay.Aims
Methods
This study examined the relationship between obesity (OB) and osteoporosis (OP), aiming to identify shared genetic markers and molecular mechanisms to facilitate the development of therapies that target both conditions simultaneously. Using weighted gene co-expression network analysis (WGCNA), we analyzed datasets from the Gene Expression Omnibus (GEO) database to identify co-expressed gene modules in OB and OP. These modules underwent Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment and protein-protein interaction analysis to discover Hub genes. Machine learning refined the gene selection, with further validation using additional datasets. Single-cell analysis emphasized specific cell subpopulations, and enzyme-linked immunosorbent assay (ELISA), protein blotting, and cellular staining were used to investigate key genes.Aims
Methods
The role of N,N-dimethylformamide (DMF) in diabetes-induced osteoporosis (DM-OS) progression remains unclear. Here, we aimed to explore the effect of DMF on DM-OS development. Diabetic models of mice, RAW 264.7 cells, and bone marrow macrophages (BMMs) were established by streptozotocin stimulation, high glucose treatment, and receptor activator of nuclear factor-κB ligand (RANKL) treatment, respectively. The effects of DMF on DM-OS development in these models were examined by micro-CT analysis, haematoxylin and eosin (H&E) staining, osteoclast differentiation of RAW 264.7 cells and BMMs, H&E and tartrate-resistant acid phosphatase (TRAP) staining, enzyme-linked immunosorbent assay (ELISA) of TRAP5b and c-terminal telopeptides of type 1 (CTX1) analyses, reactive oxygen species (ROS) analysis, quantitative reverse transcription polymerase chain reaction (qRT-PCR), Cell Counting Kit-8 (CCK-8) assay, and Western blot.Aims
Methods
Despite the interest in the association of gut microbiota with bone health, limited population-based studies of gut microbiota and bone mineral density (BMD) have been made. Our aim is to explore the possible association between gut microbiota and BMD. A total of 3,321 independent loci of gut microbiota were used to calculate the individual polygenic risk score (PRS) for 114 gut microbiota-related traits. The individual genotype data were obtained from UK Biobank cohort. Linear regressions were then conducted to evaluate the possible association of gut microbiota with L1-L4 BMD (n = 4,070), total BMD (n = 4,056), and femur total BMD (n = 4,054), respectively. PLINK 2.0 was used to detect the single-nucleotide polymorphism (SNP) × gut microbiota interaction effect on the risks of L1-L4 BMD, total BMD, and femur total BMD, respectively.Aims
Methods