The pathogenesis of atherosclerosis has been partly acknowledged to result from aberrant epigenetic mechanisms. Accordingly, low folate levels are considered to be a contributing factor to promoting vascular disease because of deregulation of DNA methylation. We hypothesized that increasing the levels of folic acid may act via an epigenetic gene silencing mechanism to ameliorate atherosclerosis. Here, we investigated the atheroprotective effects of folic acid and the resultant methylation status in high-fat diet-fed ApoE knockout mice and in oxidized low-density lipoprotein-treated human umbilical vein endothelial cells. We analyzed atherosclerotic lesion histology, folate concentration, homocysteine concentration, S-adenosylmethionine (SAM) and S-adenosylhomocysteine (SAH), and DNA methyltransferase activity, as well as monocyte chemotactic protein-1 (MCP1) and vascular endothelial growth factor (VEGF) expression and promoter methylation. Folic acid reduced atherosclerotic lesion size in ApoE knockout mice. The underlying folic acid protective mechanism appears to operate through regulating the normal homocysteine state, upregulating the SAM: SAH ratio, elevating DNA methyltransferase activity and expression, altering MCP1 and VEGF promoter methylation, and inhibiting MCP1 and VEGF expression. We conclude that folic acid supplementation effectively prevented atherosclerosis by modifying DNA methylation through the methionine cycle, improving DNA methyltransferase activity and expression, and thus changing the expression of atherosclerosis-related genes.

Background: Hashimoto’s thyroiditis (HT) is an autoimmune thyroid disease characterized by the presence of antibodies against thyroid-specific antigens. Dietary sodium intake has been implicated in the development of several autoimmune diseases, but its association with HT remains unclear.Methods: This study investigates the relationship between dietary sodium density (the ratio of sodium to energy intake) and HT using data from the National Health and Nutrition Examination Survey (NHANES) from 2007 to 2012. A cross-sectional study was conducted using NHANES data, focusing on adults aged 20 years and older with available dietary and thyroid profile data. Sodium density was calculated from two 24-h dietary recall interviews. Logistic regression models were used to evaluate the associations of sodium density with HT, thyroid peroxidase antibody (TPOAb) and thyroglobulin antibody (TgAb). Restricted cubic spline (RCS) analyses were performed to explore non-linear relationships.Results: A total of 6,258 participants were included, with 576 (9.20%) diagnosed with HT. An additional unit of dietary sodium density was associated with a 24% increased risk of HT (OR 1.24, 95% CI 1.01–1.50) in adjusted model. A breakpoint at 2.43 mg/kcal in dietary sodium density was identified using a piecewise regression model. Below this threshold, HT risk increased with rising sodium density, while above it, the risk plateaued. Higher sodium density was also associated with increased TPOAb positivity (OR 1.28, 95% CI 1.05–1.56), but not TgAb positivity.Conclusion: Elevated dietary sodium density is associated with an increased risk of HT and TPOAb positivity, suggesting that sodium intake may play a role in the pathogenesis of HT.

This study aims to develop and validate a nomogram-based risk assessment model for predicting high-risk individuals with depression in middle-aged and elderly populations. Data from the China health and retirement longitudinal study (CHARLS) in 2013 and 2018 were used to construct training cohort and validation cohorts. Spearman correlation analysis, LASSO regression, univariate and multivariate regression analyses were performed to select features, and the significant features were included in the nomogram model construction. The model was evaluated using calibration curves, ROC curves, and clinical decision curve analysis in the training, internal validation, and external validation cohorts to assess its predictive performance and clinical utility. The final selected features included gender, alcohol consumption, health status (self-rated health), life satisfaction, sleep disorders, activities of daily living score, cognition, hearing, and pain, which were used to construct the nomogram model. The AUC values of the model in the training, internal validation, and external validation cohorts were 0.823, 0.823, and 0.819, respectively. The calibration curves showed good consistency between the predicted and actual values, and the clinical decision curves indicated good clinical utility of the model. An interactive dynamic nomogram web application was also developed, allowing users to manually input variable values and instantly obtain predicted probabilities with confidence intervals, thereby enhancing the model’s clinical usability and interpretability. The nomogram model developed in this study effectively predicts individuals at risk of depression in middle-aged and elderly populations, with good predictive performance and clinical utility. This model could assist in early screening and intervention for high-risk individuals, thereby reducing the burden of depression.

The aim of this study is to explore a novel classification and investigate the clinical significance of hepatocellular carcinoma (HCC) cells. We analyzed integrated single-cell RNA sequencing and bulk RNA-seq data obtained from HCC samples. Cell trajectory analysis divided HCC cells into three subgroups with different differentiation states: state 1 was closely related to phosphoric ester hydrolase activity, state 2 was involved in eukaryotic initiation factor 4E binding, translation regulator activity and ribosome, and state 3 was associated with oxidoreductase activity and metabolism. Three molecular classes based on HCC differentiation-related genes (HDRGs) from HCC samples were identified, which revealed immune checkpoint gene expression and overall survival (OS) of HCC patients. Moreover, a prognostic risk scoring (RS) model was generated based on eight HDRGs, and the results showed that the OS of the high-risk group was worse than that of the low-risk group. Further, potential therapeutic drugs were screened out based on eight prognostic RS-HDRGs. This study highlights the importance of HCC cell differentiation in immunotherapy, clinical prognosis, and potential molecular-targeted drugs for HCC patients, and proposes a direction for the development of individualized treatments for HCC.