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Background The long-term complications of gestational diabetes mellitus (GDM) may be associated with the development of arthritis, particularly rheumatoid arthritis (RA) and osteoarthritis (OA). However, the possible relationship between these two conditions remains unclear, hindering our understanding of both diseases. We conducted a novel study using bidirectional two-sample Mendelian randomization to explore the potential causal bidirectional relationship between GDM and arthritis. Methods In this study, we extracted single nucleotide polymorphisms closely associated with GDM and arthritis (RA, OA) from published genome-wide association studies (GWAS) data in open databases as instrumental variables (IVs). We employed inverse variance-weighted as the main evaluation criterion, the weighted median method as a possible alternative criterion, and multiple methods as supplements to assess causal relationships. Results were presented as odds ratios (ORs). Additionally, leave-one-out sensitivity analysis, horizontal pleiotropy, and heterogeneity tests were used to verify the reliability and stability of the results. Result Our results indicate a causal association between GDM and an increased risk of arthritis (RA: OR = 4.34, 95% CI = 3.49–5.41, P = 1.96 × 10–39, OA: OR = 1.05, 95% CI = 1.02–1.07, P = 5.27 × 10− 05). In reverse MR analysis, our findings supported the promoting effect of RA on the development of GDM (OR = 1.15, 95% CI = 1.11–1.20, P = 4.44 × 10–14), while the evidence is insufficient to support the conclusion that OA affects the development of GDM (P = 0.757). The heterogeneity test, horizontal pleiotropy test, and leave-one-out sensitivity analysis demonstrated the reliability and stability of our study's results. Conclusion Our study suggests that genetically predisposed GDM increases the risk of developing arthritis (OA, RA). Additionally, genetically predisposed RA is causally associated with an increased risk of GDM. However, we did not find evidence for a causal association between genetically predisposed OA and GDM. These results contribute to a better understanding of the underlying mechanisms of GDM and arthritis. Furthermore, our study has significant potential to guide clinical management and the prevention of complications in patients with GDM and arthritis.

Background： The relationship between ankylosing spondylitis (AS) and mechanical complications of prosthesis after arthroplasty has garnered increasing attention in the medical community. However, the causal relationship between them remains unclear. We conducted a novel study utilizing a two-sample Mendelian randomization analysis to investigate the relationship between these two diseases. Methods: In this study, we obtained single-nucleotide polymorphisms (SNPs) strongly associated with AS and mechanical complications of prosthesis from summary data from genome-wide association studies (GWAS). AS was used as exposure and SNPs as instrumental variables (IVs). The causality was assessed using inverse variance weighted method, and the results were presented as odds ratios (OR). In addition, we conducted heterogeneity tests, horizontal pleiotropy tests, and sensitivity analysis to investigate the potential existence of any bias that may impact the causal relationship. Results: Our results indicate that AS has a causal effect that promotes mechanical complications of prosthesis, as assessed by the inverse variance weighted (IVW) method (OR= 1.037, 95% CI = 1.011, 1.062; P = 0.00366). Although the results of other methods such as MR Egger, weighted median, simple mode， and weighted mode showed no significant causal relationship between the two diseases (P > 0.05), the IVW results should be considered the primary criterion of causality, indicating that AS is a facilitator of mechanical complications of prosthesis. Heterogeneity tests, horizontal pleiotropy tests, and sensitivity analysis showed that these results are reliable and stable. Conclusion: In a word, the results of this Mendelian randomized study suggest that ankylosing spondylitis is associated with an increased risk of mechanical complications of prosthesis after arthroplasty. Therefore, it is recommended that AS patients undergo careful assessment and monitoring during the surgical process to minimize the risk of such complications.

Background Osteonecrosis of the femoral head (ONFH) is a common orthopedic disease that is characterized by the interruption of blood supply to the femoral head. This leads to ischemia of the internal tissues, subchondral bone fractures, necrosis, and ultimately, the collapse of the weight-bearing portion of the femoral head, resulting in severe functional impairment, pain, and even disability of the hip joint. Currently, available animal models of ONFH are limited in their ability to accurately replicate the natural progression of the disease. Therefore, there is a need for the development of a new animal model that can better simulate the localized pressure on the human femoral head to facilitate research related to ONFH.Method In this study, we have developed a novel method for modeling ONFH that incorporates stress factors into the modeling process using 3D printing technology and principles of biomechanics. 36 animals were randomly assigned to six groups and received either a novel modeling technique or traditional hormone induction. Following an 8-week treatment period, Micro CT scans and histological evaluations were conducted to assess tissue outcomes.Results The new model effectively replicates the pathological features of ONFH, including femoral head collapse, with a large number of empty bone lacunae observed, cartilage defects, and subchondral bone fractures in the subchondral bone region. Furthermore, the new model shows the ability to simulate the progression of the disease, making it a valuable tool for research in this field.Conclusion In conclusion, our study provides evidence that the new ONFH model is a useful tool for simulating the disease and can contribute to the development of better treatment strategies for this debilitating condition. It holds great promise for advancing our understanding of the pathogenesis of ONFH and the potential therapeutic interventions for this challenging clinical problem.

Inflammatory bone destruction has gradually attracted attention worldwide and has been observed in several kinds of pathological bone diseases, such as osteoarthritis, osteomyelitis, rheumatic arthritis, and other infectious clinical trials in the skeletal system. In this regard, excessive osteoclasts and bone resorption activity participate in osteolytic processes. Thus, negatively modulating osteoclast differentiation and bone erosion has been considered an effective therapeutic strategy to limit the poor progression of inflammatory osteolysis. Astragalin (AST) is a bioactive component of traditional Chinese drugs, such as Rosa agrestis, which presents anti-inflammatory and antioxidant effects. However, it is unclear how AST may play an essential role in regulating the dynamic balance of the bone matrix by affecting osteoclastogenesis. This study found that AST could inhibit osteoclastic formation and bone resorption activity in a dose-dependent manner without cytotoxicity. Administration of AST also inhibited the expression of cathepsin K, c-Fos, NFATc1, and TRAP at different stages of mRNA and protein levels during osteoclastogenesis. Reactive oxygen species (ROS) signalling could also be modulated by treatment with AST during RANKL-induced osteoclast differentiation through the Nrf2-HO1 signalling pathway. Additionally, AST could negatively regulate mitogen-activated protein kinase (MAPK) signalling in this process. In vivo, AST significantly reduced lipopolysaccharide (LPS)-induced bone loss in an osteolytic mouse model. AST might be a promising therapeutic candidate for treating osteolytic bone diseases in the future.

In our previous study, we reported that the long noncoding RNA, LMO7 downstream neighbor (LMO7DN), has a strong prognostic value in lung adenocarcinoma (LUAD). In this study, we further investigated the role of LMO7DN in LUAD progression. LMO7DN was found to be expressed at low levels in LUAD tissues, and its high expression predicted good prognosis. Bioinformatics analysis indicated that LMO7DN was closely associated with the cell cycle. Furthermore, we found that cell proliferation was significantly enhanced following knockdown of LMO7DN, and the number of cells in the G2/M phase was markedly decreased, whereas there was no change in apoptosis. Thus, LMO7DN inhibits cell proliferation by affecting the cell cycle and is of significant prognostic value in LUAD.