This study aimed to find potential diagnostic markers for osteoarthritis (OA) and analyze the role of immune cells infiltration in this pathology. We used OA datasets from the Gene Expression Omnibus database. First, R software was used to identify differentially expressed genes (DEGs) and perform functional correlation analysis. Then least absolute shrinkage and selection operator (LASSO) logistic regression and support vector machine-recursive feature elimination algorithms were used to screen and verify the diagnostic markers of OA. Finally, CIBERSORT was used to evaluate the infiltration of immune cells in OA tissues, and the correlation between diagnostic markers and infiltrating immune cells was analyzed. A total of 458 DEGs were screened in this study. GRB10 and E2F3 (AUC = 0.962) were identified as diagnostic markers of OA. Immune cell infiltration analysis found that resting mast cells, T regulatory cells, CD4 memory resting T cells, activated NK cells, and eosinophils may be involved in the OA process. In addition, GRB10 was correlated with NK resting cells, naive CD4 + T cells, and M1 macrophages, while E2F3 was correlated with resting mast cells. In conclusion, GRB10 and E2F3 can be used as diagnostic markers of osteoarthritis, and immune cell infiltration plays an important role in the occurrence and progression of OA.

The glutamine synthetase (GS), an astrocyte-specific enzyme, is involved in lipopolysaccharide (LPS)-induced inflammation which activates the mitogen-activated protein kinase (MAPK) signaling. Endocannabinoid 2-arachidonyl glycerol (2-AG) has been described to serve as an endogenous mediator of analgesia and neuroprotection. However, whether 2-AG can directly influence astrocytic GS and MAPK expressions remains unknown. In the present study, the effects of 2-AG on astrocytic GS expression, p38 and ERK1/2 expression, cell viability, and apoptosis following LPS exposure were investigated. The results revealed that LPS exposure increased GS expression with p38 activation in the early phase and decreased GS expression with activation of ERK1/2, decrease of cell viability, and increase of apoptosis in the late phase. Inhibition of p38 reversed GS increase in the early phase while inhibition of ERK1/2 reversed GS decrease in the late phase induced by LPS exposure. 2-AG protected astrocytes from increase of apoptosis and decrease of cell viability induced by the late phase of LPS exposure. In the early phase of LPS exposure, 2-AG could suppress the increase of GS expression and activation of p38 signaling. In the late phase of LPS exposure, 2-AG could reverse the decrease of GS expression and activation of ERK1/2 induced by LPS. These findings suggest that 2-AG could maintain the GS expression in astrocytes to a relatively stable level through modulating MAPK signaling and protect astrocytes from LPS exposure.

Background: Nucleolar and spindle-associated protein 1 (NUSAP1) was previously reported to be associated with poor prognosis in multiple cancers. In the present study, we comprehensively investigated the clinicopathological features and potential prognostic value of NUSAP1 in cervical squamous cell carcinoma and endocervical adenocarcinoma (CESC).

Pancreatic cancer (PC) is one of the most malignant tumors. Despite considerable progress in the treatment of PC, the prognosis of patients with PC is poor. The aim of this study was to identify potential biomarkers for the diagnosis and prognosis of PC. First, the original data of three independent mRNA expression datasets were downloaded from the Gene Expression Omnibus and The Cancer Genome Atlas databases and screened for differentially expressed genes (DEGs) using the R software. Subsequently, Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes pathway enrichment analyses of the DEGs were performed, and a protein‐protein interaction (PPI) network was constructed to screen for hub genes. The hub genes were analyzed for genetic variations, as well as for survival, prognostic, and diagnostic value, using the cBioPortal and Gene Expression Profiling Interactive Analysis (GEPIA) databases and the pROC package. After screening for potential biomarkers, the mRNA and protein levels of the biomarkers were verified at the tissue and cellular levels using the Cancer Cell Line Encyclopedia, GEPIA, and the Human Protein Atlas. As a result, a total of 248 DEGs were identified. The GO terms enriched in DEGs were related to the separation of mitotic sister chromatids and the binding of the spindle to the extracellular matrix. The enriched pathways were associated with focal adhesion, ECM‐receptor interaction, and phosphatidylinositol 3‐kinase (PI3K)/AKT signaling. The top 20 genes were selected from the PPI network as hub genes, and based on the analysis of multiple databases, MCM2 and NUSAP1 were identified as potential biomarkers for the diagnosis and prognosis of PC. In conclusion, our results show that MCM2 and NUSAP1 can be used as potential biomarkers for the diagnosis and prognosis of PC. The study also provides new insights into the underlying molecular mechanisms of PC.