ObjectiveAn analysis of the relationship between rheumatoid arthritis (RA) and copper death-related genes (CRG) was explored based on the GEO dataset.MethodsBased on the differential gene expression profiles in the GSE93272 dataset, their relationship to CRG and immune signature were analysed. Using 232 RA samples, molecular clusters with CRG were delineated and analysed for expression and immune infiltration. Genes specific to the CRGcluster were identified by the WGCNA algorithm. Four machine learning models were then built and validated after selecting the optimal model to obtain the significant predicted genes, and validated by constructing RA rat models.ResultsThe location of the 13 CRGs on the chromosome was determined and, except for GCSH. LIPT1, FDX1, DLD, DBT, LIAS and ATP7A were expressed at significantly higher levels in RA samples than in non-RA, and DLST was significantly lower. RA samples were significantly expressed in immune cells such as B cells memory and differentially expressed genes such as LIPT1 were also strongly associated with the presence of immune infiltration. Two copper death-related molecular clusters were identified in RA samples. A higher level of immune infiltration and expression of CRGcluster C2 was found in the RA population. There were 314 crossover genes between the 2 molecular clusters, which were further divided into two molecular clusters. A significant difference in immune infiltration and expression levels was found between the two. Based on the five genes obtained from the RF model (AUC = 0.843), the Nomogram model, calibration curve and DCA also demonstrated their accuracy in predicting RA subtypes. The expression levels of the five genes were significantly higher in RA samples than in non-RA, and the ROC curves demonstrated their better predictive effect. Identification of predictive genes by RA animal model experiments was also confirmed.ConclusionThis study provides some insight into the correlation between rheumatoid arthritis and copper mortality, as well as a predictive model that is expected to support the development of targeted treatment options in the future.

Background Keratinocytes and fibroblasts represent the major cell types in the epidermis and dermis of the skin and play a significant role in maintenance of skin homeostasis. However, the biological characteristics of keratinocytes and fibroblasts remain to be elucidated. The purpose of this study was to compare the gene expression pattern between keratinocytes and fibroblasts and to explore novel biomarker genes so as to provide potential therapeutic targets for skin-related diseases such as burns, wounds, and aging. Methods Skin keratinocytes and fibroblasts were isolated from newborn mice. To fully understand the heterogeneity of gene expression between keratinocytes and fibroblasts, differentially expressed genes (DEGs) between the two cell types were detected by RNA-seq technology. Quantitative real-time polymerase chain reaction (qRT-PCR) was used to detect the known genes of keratinocytes and fibroblasts and verify the RNA-seq results. Results Transcriptomic data showed a total of 4309 DEGs (fold-change > 1.5 and q-value < 0.05). Among them, 2197 genes were highly expressed in fibroblasts and included 10 genes encoding collagen, 16 genes encoding transcription factors, and 14 genes encoding growth factors. Simultaneously, 2112 genes were highly expressed in keratinocytes and included 7 genes encoding collagen, 14 genes encoding transcription factors, and 8 genes encoding growth factors. Furthermore, we summarized 279 genes specifically expressed in keratinocytes and 33 genes specifically expressed in fibroblasts, which may represent distinct molecular signatures of each cell type. Additionally, we observed some novel specific biomarkers for fibroblasts such as Plac8 (placenta-specific 8), Agtr2 (angiotensin II receptor, type 2), Serping1 (serpin peptidase inhibitor, clade G, member 1), Ly6c1 (lymphocyte antigen 6 complex, locus C1), Dpt (dermatopontin), and some novel specific biomarkers for keratinocytes such as Ly6a (lymphocyte antigen 6 complex, locus A) and Lce3c (late cornified envelope 3C), Ccer2 (coiled-coil glutamate-rich protein 2), Col18a1 (collagen, type XVIII, alpha 1) and Col17a1 (collagen type XVII, alpha 1). In summary, these data provided novel identifying biomarkers for two cell types, which can provide a resource of DEGs for further investigations.

Clinical treatment of Osteoarthritis (OA) remains a challenge due to the poor self‐regeneration ability of cartilage. Deer antler is the only cartilage tissue that can completely regenerate each year. Insulin‐like growth factor 1 (IGF‐1) is one of the major active components in the deer antler that participate in regulating the rapid regeneration of deer antler cartilage. This has led us to speculate that deer IGF‐1 might potentially become a candidate drug for reducing damage and inflammation of OA. Thus, we aimed to explore the underlying mechanism of deer IGF‐1 in chondrocyte proliferation, differentiation, and inflammation response. Deer, mouse, and human IGF‐1 amino acid sequences and protein structures were aligned using CLUSTAL and PSIPRED. The underlying molecular mechanism of deer IGF‐1 on primary chondrocytes was investigated by RNA‐sequencing (RNA‐seq) technology combined with various experiments. Cytokine interleukin‐1β (IL‐1β) was used to induce the inflammation response of primary chondrocytes. We found that deer IGF‐1 was more similar to human IGF‐1 than mouse IGF‐1. qRT‐PCR and immunofluorescence assay indicated that deer IGF‐1 had stronger effects than mouse IGF‐1. We also found that the deer IGF‐1 enhanced the expression of cell proliferation, differentiation, and extracellular matrix (ECM)‐related genes, but decreased the expression of ECM‐degrading genes. Deer IGF‐1 also attenuated the IL‐1β‐induced inflammatory and ECM degradation in chondrocytes. This study provides insight into the molecular mechanisms of deer IGF‐1 on primary chondrocyte viability and presents a candidate for combatting inflammatory responses in OA development.

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Background Delayed union of most tibial fractures due to their special anatomical structures.So an effective animal model is very important to study the mechanism and method of fracture healing.However, due to the small tibia of mice, the operation is difficult, and the surgical model requires high surgical skills. The construction of the fixation model of intramedullary nail for this fracture has improved and simplified the traditional fixation model of intramedullary nail, which not only achieves the purpose of constructing the fracture model, but also makes it more simple and effective.Therefore, the aim of the current study was to develop a new mouse model to study fracture healing of tibia. Methods We chose a combination between an open osteotomy and intramedullary stabilization. The 22G needle was inserted into the fracture end in a closed manner by using an open approach for osteotomy at the middle and lower 1/3 level of the tibia.Fractured tibia were analyzed using microcomputed tomography and histology at days 7,14,21and 28after surgery. All animals displayed normal limb loading and a physio-logical gait pattern within the first three days after fracture. No animals were lost due to surgery or anesthesia. Results X-ray confirmed that the fracture types obtained by the fracture modeling method were transverse fractures. X-ray, Micro-CT, immunohistochemistry, histological staining and Real-time PCR showed that the fracture healing of mice was typical endochondral ossification, with high repeatability. Conclusion The mouse tibial fracture model established by intramedullary nailing is safe, rapid and simple. Its fracture healing is a typical intrachondral ossification with high repeatability, which can be better used for the study of molecular mechanism and clinical transformation of fracture healing and bone metabolism.