Jiangxi Maternal and Child Health Hospital

This study aimed to investigate the mediating effect of self-efficacy and perceived stress on the relationship between depression and subjective memory complaints (SMC) among patients with depression. A cross-sectional survey was conducted with Chinese patients experiencing SMC. The assessment of SMC, depression, self-efficacy and perceived stress was performed using the Subjective Cognitive Decline Questionnaire-9, Hamilton Depression Rating Scale-17, General Self-efficacy Scale and the Chinese version of the Perceived Stress Scale. Pearson correlation analysis was utilised to examine the correlations among these variables. AMOS 26.0 was employed to construct a chain mediation model, and the mediating effects of this model were tested using the bootstrap method. A total of 372 patients with depression voluntarily participated in the questionnaires during their leisure time, and 343 valid questionnaires were recovered. The analysis indicated that SMC significantly affected the depression of patients (β = 0.211, critical ratio = 3.915, p < 0.001). Lower self-efficacy and higher perceived stress were associated with increased depression. Specifically, self-efficacy and perceived stress continuously mediated the relationship between SMC and depression, with an overall mediating effect value of 0.209. After including self-efficacy and perceived stress, the total effect of SMC on depression was found to be 0.420. This study highlights the collective contributions of SMC, self-efficacy and perceived stress to depression. Self-efficacy and perceived stress continuously mediate the association between depression and SMC, indicating that depressed patients with SMC exhibit lower self-efficacy; additionally, reduced self-efficacy may exacerbate perceived stress, ultimately leading to elevated levels of depression. These findings underscore the importance of developing self-efficacy and stress coping strategies. Enhancing self-efficacy and reducing perceived stress can alleviate SMC in patients with depression and improve overall cognitive function. Regular monitoring and intervention for self-efficacy and perceived stress in patients with SMC are crucial for assessing and screening subclinical depression patients, initiating early interventions to alleviate depression and promoting mental health.

International Practice Guidelines Registry Platform (PREPARE-2024CN606).

This study aimed to investigate the association between serum uric acid level before gestational age of 20 weeks and preeclampsia. This study included pregnant women of three hospitals from January 2018 to June 2024. Clinical data were extracted using electronic medical record systems. The exposure factor was serum uric acid measured before gestational age of 20 weeks, with the primary outcome being preeclampsia, and secondary outcomes being preterm birth. Smooth curve fitting, ROC analysis, threshold effects, multivariate logistic regression, and subgroup analysis were employed to examine the relationship between uric acid and preeclampsia. The Kaplan-Meier method and log-rank test were used to evaluate the impact of serum uric acid on the gestational age at delivery. A total of 44,609 singleton pregnancies were included. There was a nonlinear relationship between serum uric acid level and the risk of preeclampsia, with a turning point at a uric acid level of 240 µmol/L. After adjusting for confounders, compared to non-preeclampsia cases, the risk of preeclampsia increased 1.38 times (95% CI: 1.28-1.48) for uric acid level between 240~360 µmol/L and 2.14 times (95% CI: 1.61-2.85) for UA levels ≥ 360 µmol/L. Similar positive associations were observed between uric acid level and preterm birth. Subgroup analysis maintained this positive correlation. Interaction tests indicated that BMI might influence the strength of the association between uric acid and preeclampsia (P < 0.05). Elevated serum uric acid level before gestational age of 20 weeks increase the risk of preeclampsia. Elevated uric acid levels in early pregnancy are associated with an increased risk of preeclampsia, suggesting that monitoring uric acid may help identify women at higher risk.

Breast cancer is one of the most prevalent malignancies among women. Although the impact of age on breast cancer progression is well documented, the role of aberrant alternative splicing events in older adults breast cancer patients remains poorly understood. Here, we identified that older adults breast cancer patients exhibit a higher frequency of aberrant alternative splicing events compared to younger patients using public database, a finding that was further validated by data from FUSCC cohorts. A total of 390 high-variability-specific splicing events were observed exclusively in older adults patients. The unsupervised clustering analysis revealed the existence of three distinct subtypes of older adults patients, each displaying significantly different immune cell infiltration profiles and prognostic outcomes. To identify the key regulatory factors of these splicing subtypes, we conducted AS activity score analysis and identified 68 RNA-binding proteins as potential modulators. Subsequently, a machine learning approach using SelectKBest-SVM was employed to construct a predictive model, which demonstrated optimal performance in predicting the prognosis of older adults breast cancer patients, with a high AUC and validation on an independent test set. The developed predictive model offers a promising tool for personalized treatment strategies and accurate prognostication, advancing precision medicine for older adults breast cancer patients.