Role of immune cell infiltration and small molecule drugs in adhesive capsulitis: Novel exploration based on bioinformatics analyses

Rat models of frozen shoulder: Classification and evaluation

Frozen shoulder (FS), also known as adhesive capsulitis, is a condition that causes contraction and stiffness of the shoulder joint capsule. The main symptoms are persistent shoulder pain and a limited range of motion in all directions. These symptoms and poor prognosis affect people's physical health and quality of life. Currently, the specific mechanisms of FS remain unclear, and there is variability in treatment methods and their efficacy. Additionally, the early symptoms of FS are difficult to distinguish from those of other shoulder diseases, complicating early diagnosis and treatment. Therefore, it is necessary to develop and utilize animal models to understand the pathogenesis of FS and to explore treatment strategies, providing insights into the prevention and treatment of human FS. This paper reviews the rat models available for FS research, including external immobilization models, surgical internal immobilization models, injection modeling models, and endocrine modeling models. It introduces the basic procedures for these models and compares and analyzes the advantages, disadvantages, and applicability of each modeling method. Finally, our paper summarizes the common methods for evaluating FS rat models.

Impact of immune cells on the risk of frozen shoulder: A 2-sample Mendelian randomization study

The pathogenesis of frozen shoulder (FS) remains unclear, and current research primarily focuses on immune responses. Increasing evidence suggests that immune cells play a significant role in FS development. However, the causal relationship between the two remains poorly understood. Therefore, we aimed to investigate this using Mendelian randomization (MR) analysis. Single nucleotide polymorphisms closely associated with 731 immune phenotypes were obtained from publicly available GWAS datasets as instrumental variables. FS was used as the outcome with a sample size of 451,099 cases. Causal effects were analyzed using the inverse variance-weighted method. We conducted sensitivity tests, including the intercept of the MR-Egger and MR-PRESSO analyses. The presence of heterogeneity was evaluated using Cochran Q test. We identified potential causal relationships in terms of increased risk for FS with 5 immune phenotypes: CD25++ CD45RA+ CD4 not regulatory T cell %CD4+ T cells (odds ratio [OR] = 1.0273, 95% confidence interval [CI]: 1.0093-1.0457, P = .0028), CD25++ CD45RA+ CD4 not regulatory T cell %T cell (OR = 1.0240, 95% CI: 1.0057-1.0427, P = .0098), CD127 on CD28+ CD4+ T cells (OR = 1.0398, 95% CI: 1.0121-1.0682, P = .0046), CD4 on human leukocyte antigen DR+ CD4+ T cells (OR = 1.0795, 95% CI: 1.0316-1.2195, P = .0009), and human leukocyte antigen DR on CD14- CD16+ monocytes (OR = 1.0533, 95% CI: 1.0136-1.0945, P = .0081). Few significant heterogeneities or horizontal pleiotropies were observed. Through MR analysis, we identified distinct 5 types of immune cells that were positively correlated with the occurrence and development of FS, providing guidance for clinical intervention in FS.

Exploring the association between rosacea and acne by integrated bioinformatics analysis

Clinically, rosacea occurs frequently in acne patients, which hints the existence of shared signals. However, the connection between the pathophysiology of rosacea and acne are not yet fully understood. This study aims to unveil molecular mechanism in the pathogenesis of rosacea and acne. We identified differentially expressed genes (DEGs) by limma and weighted gene co-expression network analysis and screened hub genes by constructing a protein-protein interaction network. The hub genes were verified in different datasets. Then, we performed a correlation analysis between the hub genes and the pathways. Finally, we predicted and verified transcription factors of hub genes, performed the immune cell infiltration analysis using CIBERSORT, and calculated the correlation between hub genes and immune cells. A total of 169 common DEGs were identified, which were mainly enriched in immune-related pathways. Finally, hub genes were identified as IL1B, PTPRC, CXCL8, MMP9, CCL4, CXCL10, CD163, CCR5, CXCR4, and TLR8. 9 transcription factors that regulated the expression of hub genes were identified. The infiltration of γδT cells was significantly increased in rosacea and acne lesions and positively linked with almost all hub genes. These identified hub genes and immune cells may play a crucial role in the development of rosacea and acne.