Objective To explore the potential mechanism of the occurrence and development of lupus nephritis (LN) and identify key biomarkers and immune-related pathways associated with the progression of LN. Methods We downloaded a dataset from the Gene Expression Omnibus database. By analyzing the differential expression of genes and performing weighted gene co-expression network analysis (WGCNA), as well as Gene Ontology enrichment, Disease Ontology enrichment, and Kyoto Encyclopedia of Genes and Genomes pathway enrichment, we explored the biological functions of differentially expressed genes in LN. Using three machine learning models, namely LASSO regression, support vector machine, and random forest, we identified the hub genes in LN, and constructed a line diagram diagnosis model based on the hub genes. The diagnostic accuracies of the hub genes were evaluated using the receiver operating characteristic curve, and the relationship between known marker gene sets and hub gene expression was analyzed using single sample gene set enrichment analysis. Results We identified a total of 2297 differentially expressed genes. WGCNA generated 7 co-expression modules, among which the cyan module had the highest correlation with LN. We obtained 347 target genes by combining differential genes. Using the three machine learning methods, LASSO regression, support vector machine, and random forest, we identified three hub genes (CLC, ADGRE4P, and CISD2) that could serve as potential biomarkers for LN. The area under the receiver operating characteristic curve (AUC) analysis showed that these three hub genes had significant diagnostic value (AUCCLC=0.718, AUCADGRE4P=0.813, AUCCISD2=0.718). According to single sample gene set enrichment analysis, the hub genes were mainly associated with apoptosis, glycolysis, metabolism, hypoxia, and tumor necrosis factor-α-nuclear factor-κB-related pathways. Conclusions By combining WGCNA and machine learning techniques, three hub genes (CLC, ADGRE4P, and CISD2) that may be involved in the occurrence and development of LN are identified. These genes have the potential to aid in the early clinical diagnosis of LN and provide insight into the mechanisms underlying LN progression.
Objective To explore the mental health status and influencing factors of clinical medical students pursuing a professional master’s degree under the “dual-track integration” training systems. Methods Clinical medical students pursuing a professional master’s degree who underwent residency standardized training in 123 hospitals from different areas of China were selected as the research objects from May 28th to June 4th, 2024, and the mental health and stress were investigated by questionnaire. Results A total of 1195 clinical medical students pursuing a professional master’s degree were included. Symptom Checklist-90 analysis showed that 582 (48.7%) master students had mental health problems. The two-group students (with and without psychological problems) had statistical differences in exercise frequency, sleep quality, extent of staying up late, interpersonal communication, and average number of night shifts per month (P<0.001). The subjective scores of interpersonal pressure, economic pressure, love and marriage pressure, schoolwork pressure, scientific research pressure, clinical work pressure, entering higher education pressure and employment pressure, and the proportion of graduating from 985/211 university of the master students with psychological problems were significantly higher than those of the master students without psychological problems (P<0.001). Logistic regression analysis showed that poor sleep quality [odds ratio (OR)=1.626, 95% confidence interval (CI) (1.085, 2.438), P=0.019], 985/211 university degree [OR=1.448, 95%CI (1.097, 1.910), P=0.009], interpersonal pressure [OR=1.194, 95%CI (1.121, 1.272), P<0.001], love and marriage pressure [OR=1.067, 95%CI (1.014, 1.122), P=0.012] and entering higher education pressure [OR=1.110, 95%CI (1.055, 1.167), P<0.001] were independent risk factors, while the male sex [OR=0.621, 95%CI (0.472, 0.817), P=0.001] were protective factor for psychological problems of these medical students. Conclusions Under the “dual-track integration” training systems, the clinical medical students pursuing a professional master’s degree have a higher prevalence of psychological problems, especially the females and the 985/211 bachelor’s degree scholars. It is important to improve sleep quality, strengthen interpersonal interaction and reduce pressure load to improve the mental health level of these clinical medical students.