Yi Zhang

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Background: Depression and anxiety symptoms are prevalent among college students and significantly affect their academic performance, interpersonal functioning, and long-term well-being. Repeated cross-sectional surveys can reveal temporal variations in symptom burden, yet rigorous data harmonization is essential to ensure valid cross-year comparisons. This study aimed to harmonize three waves of questionnaire survey data and provide a comprehensive descriptive summary of depressive and anxiety symptoms among Chinese college students. Methods: Questionnaire submissions were recorded from 9 November 2023 to 3 January 2024, 14 May to 14 June 2024, and 7 April to 5 May 2025. Student identifiers were used to identify repeated within-wave submissions and overlap across administrations. After retaining the earliest response per student within each administration, 4,236 records remained (2023: 1,998; 2024: 1,743; 2025: 495). Depressive and anxiety symptoms were measured using the PHQ-9 and GAD-7. Inter-administration comparisons used Kruskal-Wallis and chi-square tests with effect sizes. Generalized estimating equations accounted for repeated observations of the same student. Internal consistency, PHQ-9/GAD-7 convergence, and multivariable correlates of PHQ-9 Item 9 endorsement were evaluated. Results: The analytic dataset included 4,236 wave-specific records from 2,782 unique students; 240 students participated in all three administrations. Overall mean PHQ-9 and GAD-7 scores were 5.08 ± 4.08 and 3.21 ± 3.70, respectively. Differences across administrations were statistically significant (PHQ-9 epsilon-squared = 0.006; GAD-7 epsilon-squared = 0.007). In age- and sex-adjusted GEE models, the 2024 administration had higher PHQ-9 scores than 2023 (adjusted mean difference 0.49, 95% CI 0.24–0.74), whereas the 2025 difference was not significant. PHQ-9 and GAD-7 demonstrated high internal consistency (alpha = 0.890 and 0.937) and strong convergence (Spearman rho = 0.798). Conclusion: Mild depressive and anxiety symptoms were highly prevalent in this college cohort, while moderate-to-severe symptoms affected a clinically significant minority. The temporal peak in 2024 and the persistent elevation of self-harm ideation in 2025, underscore the necessity of a tiered campus mental health strategy and the critical importance of independent, continuous suicide risk surveillance. The harmonized dataset provides a robust foundation for future longitudinal risk-factor modeling and evidence-based intervention planning.

Obesity and diabetic nephropathy (DN) represent escalating global health burdens. Glomerular mesangial cell (MC) injury, driven by lipotoxicity from free fatty acids like palmitic acid (PA), is central to DN pathogenesis. Fibroblast growth factor 21 (FGF21) regulates metabolism and mitigates obesity-related complications, yet its specific protective mechanisms against PA-induced MC injury remain unclear. This study employed a dual approach. Part I involved a cross-sectional survey of 1,067 type 2 diabetes mellitus (T2DM) patients to identify demographic and clinical risk factors for chronic kidney disease (CKD) using multivariate regression and latent class analysis. Part II utilized human MCs to investigate PA-induced apoptosis and endoplasmic reticulum stress (ERS), evaluating the therapeutic potential of recombinant human FGF21 (rhFGF21) and the involvement of the SIRT1 signaling pathway. A total of 1067 patients with T2DM were involved in the current study, among them, 345 patients with chronic kidney disease (CKD). The percent of females was 50.3%, and the mean age was 59 ± 11.3 years. Multivariate regression analysis showed that age, systolic blood pressure (SBP), duration of diabetes, hyperlipidemia and smoking status were associated with DN. We also performed a potential category analysis of these factors, and the results were derived into three groups. Further analysis found that there was a positive association between the stage of diabetes and the risk factors at high risk levels. We identified that PA increased the levels of pro-apoptotic markers (cleaved caspase-3 and BCL-2 associated X-protein), decreased the expression levels of the anti-apoptotic marker BCL-2, and upregulated the expression levels of the endoplasmic reticulum stress (ERS)-related proteins, glucose-regulated protein 78, activation transcription factor 4, and CHOP. However, all the effects were attenuated by rhFGF21 treatment. In addition, PA increased FGF21 and sirtuin 1 (SIRT1) expression levels, and rhFGF21 further upregulated SIRT1 expression. However, upon SIRT1 knockdown, rhFGF21 did not exert its protective effect on human MCs. Our findings demonstrate that rhFGF21 protects human MCs from PA-induced apoptosis and ERS via the FGF21-SIRT1 signaling cascade. Integrating these molecular insights with clinical risk stratification suggests that targeting the FGF21-SIRT1 pathway, alongside managing modifiable risk factors such as hypertension and hyperlipidemia, offers a promising integrated strategy for preventing and treating diabetic nephropathy.

Background: Polycystic ovary syndrome (PCOS) is associated with an increased risk of type 2 diabetes mellitus (T2DM), and the risk of PCOS increases in patients with T2DM of reproductive age. The bidirectional link between PCOS and T2DM has been confirmed through experimental and epidemiological evidence; however, the genetic factors that contribute to deeper insights into the shared pathogenesis of these two diseases remain unclear. We aimed to identify shared immune- and inflammation-related genes and pathways in PCOS and T2DM, further explore the molecular mechanisms in developing this comorbidity, and predict drugs with potential effects to develop novel therapeutic strategies. Methods: We obtained microarray expression profiling datasets (GSE34526 and GSE25724) of PCOS and T2DM from the Gene Expression Omnibus (GEO) database. The differential expression genes (DEGs) between disease and control groups were identified and analyzed via the R package “limma” following data preprocessing. The R package “clusterProfiler” was applied to conduct Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genome (KEGG) pathway enrichment analyses. Hub genes were identified from the protein-protein interaction (PPI) network using the Molecular Complex Detection (MCODE) and cytoHubba plug-ins of Cytoscape. Transcription factor (TF)-hub and miRNA-hub gene regulatory networks were constructed and visualized using Cytoscape. The Drug-Gene Interaction Database (DGIdb) was used to predict prospective drugs targeting hub genes. In addition, hub genes were verified by RT-qPCR. Results: A total of 239 common DEGs, including 140 upregulated genes and 99 downregulated genes, were discovered. These common DEGs were primarily associated with immune regulation and inflammatory processes. Moreover, ITGAM, ITGB2, SPI1, C1QB, CCR5, C3AR1, LY86, AIF1, and IRF8 were identified as hub genes and the RT-qPCR results showed significant differences. These hub genes were predominantly related to the regulation of neutrophil degranulation (ITGAM, ITGB2, and SPI1), dendritic cell chemotaxis (CCR5 and SPI1), follicular B cell differentiation (SPI1 and IRF8), synapse pruning (ITGAM and C1QB), integrin αM-β2 complex (ITGAM and ITGB2), the regulation of prostaglandin-E synthase activity (ITGAM and ITGB2), Staphylococcus aureus infection (ITGAM, ITGB2, C1QB, and C3AR1) and pertussis (IRF8). Finally, we predicted 19 TFs, 170 miRNAs, and 40 potential therapeutic drugs interacting with hub genes. Conclusion: We identified nine hub genes and related gene regulatory networks and discussed novel perspectives on the roles of immunity and inflammation in patients with PCOS and T2DM. Moreover, maraviroc, cenicriviroc, PF-04634817 (targeting CCR5), butein (targeting ITGB2), dimethyl sulfoxide (targeting ITGAM), and rovelizumab (targeting both ITGB2 and ITGAM) are potential therapeutic drugs. However, these findings require validation through further clinical and experimental studies.

Introduction: Identifying the causes of anxiety and depression among nursing students at an early stage is crucial for enhancing their mental health. The impact of negative life events on mental health has been insufficiently studied in nursing students, and the specific connections between these events and mental health are not yet clear. Aim: This study aimed to explore the impact of negative life events on anxiety and depression among nursing freshmen, as well as the potential mediating role of mobile phone addiction in this influence. Methods: This cross‐sectional study included 320 nursing freshmen from the School of Nursing, Anhui Medical University, China, who were enrolled using a convenience sampling method, and the response rate was 90.65%. Data were collected using the Adolescent Self‐rating Life Events Checklist (ASLEC), Mobile Phone Addiction Tendency Scale (MPATS), Generalised Anxiety Disorder‐7 (GAD‐7) and Patient Health Questionnaire‐9 (PHQ‐9). The SPSS 23.0 and AMOS 24.0 software were used for data analysis. Results: Negative life events had a significant positive predictive effect on anxiety ( β = 0.547, p < 0.001) and depression ( β = 0.603, p < 0.001), accounting for 28.6% and 34.7% of the variance, respectively. Mobile phone addiction played a mediating role in the relationship between negative life events and both anxiety and depression, mediating 34.70% and 29.06% of the total effect, respectively. Discussion: Negative life events are significant predictors of anxiety and depression among nursing freshmen, with mobile phone addiction mediating this effect. Implications for Practice: Nursing educators should incorporate mental health screening into the freshman orientation process to promptly identify and support students with tendencies towards anxiety and depression, while also fostering their ability to cope with negative life events and guiding them to develop healthy smartphone usage habits. Relevance Statement: This study highlights the pivotal role of negative life events and mobile phone addiction in the mental health of nursing freshmen, providing critical insights for mental health nursing. By identifying key predictors of anxiety and depression, our findings can inform targeted interventions to support student well‐being and resilience within nursing education programs.

Non-suicidal self-injury (NSSI) has long affected people's lives and is an important and serious public health issue, especially among college students. This study aims to identify modifiable factors, including problematic mobile phone use (PMPU) and mental health (MH), etc. Only a few studies have mentioned the correlation between PMPU and NSSI, this study focus on its association with suicide, and whether this association is moderated by chronotype and MH needs to be confirmed by research. A cross-sectional study design investigated the association between PMPU, chronotype and MH and NSSI. We collected information from participants using an electronic questionnaire that included general demographics, PMPU, NSSI, and sleep-related variables (chronotype, weekday and weekend sleep duration). Participants completed standardized questionnaires, including mobile phone addiction tendency scale (MPATS) for PMPU, the Morningness-Eveningness Questionnaire (MEQ) for chronotype, Patient Health Questionnaire (PHQ-9) for depression symptoms, Generalized Anxiety Scale (GAD-7) for anxiety symptoms, and the non-suicidal self-injury (NSSI) for suicide risk. A multivariable linear regression model measure these variables, and moderation model which using the PROCESS method examined the relationship of PMPU, chronotype and MH and NSSI. A total of 5639 adolescents were included in the study, with a mean age of 19.64 [± 0.90] years), and 46.3% of the participants were male. The prevalence of NSSI was 12.1%, in multivariate linear regression, high levels of PMPU (β = 0.362), eveningness (β = 0.665), depression (β = 1.183), and anxiety (β = 1.308) were all associated with higher NSSI, indicating a significant association. In the analysis results of moderation, chronotype and MH also moderated the relationship between PMPU and NSSI, indicating that there was a relationship between PMPU, chronotype, MH and NSSI. This study highlights the important role of PMPU and mental health in predicting NSSI. Interventions targeting these modifiable factors may help reduce the prevalence of NSSI among young adults. Improving sleep hygiene, reducing mobile phone abuse, and providing appropriate psychological support are effective strategies to prevent NSSI. Educational institutions and society should strengthen guidance on the proper use of digital media by young people, especially among college students, promote healthy lifestyles, and establish early identification and support systems to help those individuals at risk.

Autoimmune thyroid diseases (AITD) are the most common autoimmune disorders. Identifying new biomarkers and therapeutic targets in plasma proteins is crucial. We conducted a proteome-wide Mendelian randomization (MR) and colocalization analysis to determine plasma proteins causally associated with AITD. Proteome-wide summary-level genome-wide association studies (GWAS) were collected from the UK Biobank Pharma Proteomics Project (UKB-PPP) and deCODE genetics, encompassing 2922 and 4719 plasma proteins, respectively. Genetic associations with AITD were derived from an AITD GWAS meta-analysis study (30,234 cases and 725,172 controls) and the FinnGen database (40,926 cases and 274,069 controls). MR analysis, including summary-data-based Mendelian randomization (SMR), Wald Ratio, and IVW methods, was employed to estimate the causal effects between plasma proteins and AITD. Colocalization analysis was used to assess whether identified proteins and AITD shared the common causal variants. Genetically predicted levels of 11 plasma proteins were found to have a causal association with AITD. Colocalization analysis revealed that five of these proteins had evidence of colocalization, including leukemia inhibitory factor (LIF), interleukin-7 receptor subunit alpha (IL7RA), CD226, tumor necrosis factor ligand superfamily member 11 (TNF11), and transcription factor junD (JUND). Genetically predicted levels of LIF and IL7RA were associated with an increased risk of AITD, whereas CD226, TNF11, and JUND were inversely related to AITD risk. This study has identified multiple candidate plasma proteins causally associated with AITD. Among these proteins, LIF, IL7RA, CD226, TNF11, and JUND are considered to have potential as disease biomarkers and therapeutic targets, but further clinical and experimental validation is still necessary in the future.

Background: In this cross-sectional study, we aim to investigate the value of non-invasive advanced glycation end products (AGEs) detection in the early screening of diabetic nephropathy(DN) among individuals with type 2 diabetes mellitus and assess whether metabolic parameters and glycated hemoglobin A_1c (HbA_1c) can moderate this relationship.Methods: A total of 912 T2DM patients were enrolled. The urinary albumin-to-creatinine ratio (UACR) was measured in morning urine samples to assess DN. AGEs were non-invasively measured through skin autofluorescence. Recognizing the role of age in both AGEs and DN, AGE_age was calculated as AGEs × age/100 for related analyses.Results: The overall prevalence of DN in the present study was 37.2%. Elevated AGE_age(χ² = 61.06) was associated with a higher prevalence of DN. Multivariable linear regression demonstrated that AGE_age was positively associated with UACR levels(β = 0.154, 95% CI: 0.126, 0.306, P1c (HbA_1c) affected the correlation between AGE_age and UACR. Body mass index (BMI) and triglyceride glucose-body mass index (TyG-BMI) also affect the correlation between AGE_age and UACR, there were significant interactions between AGE_age, HbA_1c, BMI, TyG-BMI, and UACR.Conclusions: Complex associations and interactions were observed between AGEs, metabolic metrics, HbA_1c, and DN. Implementing comprehensive interventions can potentially benefit the prevention of DN in T2DM patients.