Unique anabolic action of stem cell gene therapy overexpressing PDGFB-DSS6 fusion protein in OVX osteoporosis mouse model

Bone-targeted lipoplex-loaded three-dimensional bioprinting bilayer scaffold enhanced bone regeneration

Clinical bone-morphogenetic protein 2 (BMP2) treatment for bone regeneration, often resulting in complications like soft tissue inflammation and ectopic ossification due to high dosages and non-specific delivery systems, necessitates research into improved biomaterials for better BMP2 stability and retention. To tackle this challenge, we introduced a groundbreaking bone-targeted, lipoplex-loaded, three-dimensional bioprinted bilayer scaffold, termed the polycaprolactone-bioink-nanoparticle (PBN) scaffold, aimed at boosting bone regeneration. We encapsulated BMP2 within the fibroin nanoparticle based lipoplex (Fibroplex) and functionalized it with DSS6 for bone tissue-specific targeting. 3D printing technology enables customized, porous PCL scaffolds for bone healing and soft tissue growth, with a two-step bioprinting process creating a cellular lattice structure and a bioink grid using gelatin-alginate hydrogel and DSS6-Fibroplex, shown to support effective nutrient exchange and cell growth at specific pore sizes. The PBN scaffold is predicted through in silico analysis to exhibit biased BMP2 release between bone and soft tissue, a finding validated by in vitro osteogenic differentiation assays. The PBN scaffold was evaluated for critical calvarial defects, focusing on sustained BMP2 delivery, prevention of soft tissue cell infiltration and controlled fiber membrane pore size in vivo. The PBN scaffold demonstrated a more than eight times longer BMP2 release time than that of the collagen sponge, promoting osteogenic differentiation and bone regeneration in a calvarial defect animal. Our findings suggest that the PBN scaffold enhanced the local concentration of BMP2 in bone defects through sustained release and improved the spatial arrangement of bone formation, thereby reducing the risk of heterotopic ossification.

Identification of combined biomarkers for predicting the risk of osteoporosis using machine learning

Osteoporosis is a severe chronic skeletal disorder that affects older individuals, especially postmenopausal women. However, molecular biomarkers for predicting the risk of osteoporosis are not well characterized. The aim of this study was to identify combined biomarkers for predicting the risk of osteoporosis using machine learning methods. We merged three publicly available gene expression datasets (GSE56815, GSE13850, and GSE2208) to obtain expression data for 6354 unique genes in postmenopausal women (45 with high bone mineral density and 45 with low bone mineral density). All machine learning methods were implemented in R, with the GEOquery and limma packages, for dataset download and differentially expressed gene identification, and a nomogram for predicting the risk of osteoporosis was constructed. We detected 378 significant differentially expressed genes using the limma package, representing 15 major biological pathways. The performance of the predictive models based on combined biomarkers (two or three genes) was superior to that of models based on a single gene. The best predictive gene set among two-gene sets included PLA2G2A and WRAP73. The best predictive gene set among three-gene sets included LPN1, PFDN6, and DOHH. Overall, we demonstrated the advantages of using combined versus single biomarkers for predicting the risk of osteoporosis. Further, the predictive nomogram constructed using combined biomarkers could be used by clinicians to identify high-risk individuals and in the design of efficient clinical trials to reduce the incidence of osteoporosis.

Advances in mesenchymal stem cell transplantation for the treatment of osteoporosis

Osteoporosis is a systemic metabolic bone disease with characteristics of bone loss and microstructural degeneration. The personal and societal costs of osteoporosis are increasing year by year as the ageing of population, posing challenges to public health care. Homing disorders, impaired capability of osteogenic differentiation, senescence of mesenchymal stem cells (MSCs), an imbalanced microenvironment, and disordered immunoregulation play important roles during the pathogenesis of osteoporosis. The MSC transplantation promises to increase osteoblast differentiation and block osteoclast activation, and to rebalance bone formation and resorption. Preclinical investigations on MSC transplantation in the osteoporosis treatment provide evidences of enhancing osteogenic differentiation, increasing bone mineral density, and halting the deterioration of osteoporosis. Meanwhile, the latest techniques, such as gene modification, targeted modification and co-transplantation, are promising approaches to enhance the therapeutic effect and efficacy of MSCs. In addition, clinical trials of MSC therapy to treat osteoporosis are underway, which will fill the gap of clinical data. Although MSCs tend to be effective to treat osteoporosis, the urgent issues of safety, transplant efficiency and standardization of the manufacturing process have to be settled. Moreover, a comprehensive evaluation of clinical trials, including safety and efficacy, is still needed as an important basis for clinical translation.