Atherosclerosis (AS) is emerging as a major global public health problem. Researchers are developing and implementing various anti-AS strategies. This study aimed to investigate gut microbiota and metabolite changes associated with elevated serum low-density lipoprotein cholesterol (LDL-c). Mice were divided into two equal groups: Group C (mice with gut microbiota from healthy subjects) and Group B (mice with gut microbiota from AS). At the end of the 8-week study, blood samples were collected for blood lipid analysis; rectal feces were collected for microbial 16S rRNA sequencing analysis and metabolomics analysis. Our results showed that the B group significantly increased serum lipid levels of LDL-c. However, no statistically significant differences were observed in the richness and diversity of the gut microbiota, but we observed an increase in the ratio of Firmicutes to Bacteroidetes and an increase in the abundance of Parabacteroides Goldstein. In addition, untargeted metabolomic analysis of fecal samples revealed 128 metabolites that were differentially expressed between groups C and B. Notably, group B was found to have significantly increased levels of metabolites involved in lipid metabolism pathways, such as estrogen glucuronide, ginsenoside f1, Pe (16:1e/14,15-epete), and prostaglandin E1. Those data highlight the importance of understanding AS from the gut microbiota perspective and establish a foundation for future research on AS.

Background: Identifying optimal housekeeping genes is essential to accurately quantify gene expression dynamics across the 18th day (male and female begin to pair) and the 23rd day (female begin to sex mature) post infection of Schistosoma japonicum, because this process involves selecting suitable housekeeping genes to ensure the reliability and accuracy of all subsequent expression analyses, thereby improving the precision of biological interpretations. Schistosoma japonicum transcriptomics reveals marked stage-dependent variation in candidate reference genes, which directly challenges the long-standing hypothesis that commonly recommended reference genes remain stably expressed throughout the 18th day and the 23rd day post-infection developmental phases and therefore emphasizes the critical need for careful selection and rigorous validation in any specific experimental context. Methods: In this study, seven widely reported genes (GAPDH, TUBA, ACTB, SOD1, TP, ND and PS) of Schistosoma japonicum were systematically validated by combining Solexa high-throughput sequence analysis with targeted qPCR experiments to identify the most suitable reference genes on the 18th day and the 23rd day post infection of Schistosoma japonicum, and the expression stability of these seven candidate genes was then comprehensively evaluated using four complementary algorithms—the ΔCT method and the GeNorm V3.5, BestKeeper, and NormFinder software applications. Results: GAPDH displayed the most consistent expression profiles, whereas TUBA exhibited the least stability, particularly at the specific time points of 18 and 23 days post infection in both paired and unpaired female Schistosoma japonicum. Conclusions: The suitability of any housekeeping gene is strongly dependent on the study’s specific context and experimental conditions. Therefore, the conclusions drawn here are explicitly limited to the developmental window of 18 and 23 days post infection. Rigorous, stage-specific validation is indispensable before reliable quantitative gene expression analyses can be performed.

Metabolic reprogramming is closely linked to tumor proliferation, invasion, and immune escape. Despite its central role in amino acid metabolism, the regulatory mechanisms of asparagine metabolism in hepatocellular carcinoma (HCC) progression remain poorly characterized. Rather than focusing on canonical metabolic genes, prognostic markers were identified from co-expression modules associated with asparagine metabolism signatures. Using the TCGA database and asparagine metabolism-related gene sets, a prognostic risk-scoring model was developed through differential expression analysis, univariate Cox regression, and the LASSO algorithm and externally validated with the GEO dataset (GSE14620). Survival analysis, ROC curve evaluation, nomogram construction, scRNA-seq, GSEA, and drug sensitivity analysis were performed to systematically delineate the molecular mechanisms by which asparagine metabolism drives HCC progression. A three-gene signature comprising BOP1, SAC3D1, and PDE2A effectively stratified patients into high- and low-risk groups. High-risk patients exhibited markedly poorer overall survival, enrichment in tumor proliferation-associated pathways, increased tumor purity, reduced immune cell infiltration, and a substantially higher TP53 mutation rate (38% vs. 13%). In contrast, the low-risk group showed enrichment in pathways linked to hepatoblastoma suppression and liver function, alongside improved predicted response to immunotherapy. Single-cell analysis identified NK cells and endothelial cells as central mediators of asparagine metabolism-driven HCC progression, with BOP1, SAC3D1, and PDE2A displaying dynamic expression patterns during differentiation. Furthermore, the high-risk group was predicted to be more sensitive to chemotherapeutics such as cyclophosphamide and 5-fluorouracil. These findings highlight a potential interplay between nitrogen metabolism and asparagine metabolism in HCC and suggest mechanisms by which these pathways may influence NK cell and endothelial cell function to promote disease progression. This study establishes a novel prognostic model and identifies potential chemotherapeutic vulnerabilities in high-risk patients, warranting further experimental and clinical validation.

Background/Objectives: Astragalus root, a traditional Chinese herbal remedy, has shown potential benefits against diabetic nephropathy (DN). However, the mechanisms driving its effects remain poorly understood. This study explored the molecular pathways through which Astragalus root improves DN. Methods: To identify possible targets and mechanisms of Astragalus root in DN treatment, we applied network pharmacology, molecular docking, molecular dynamics simulation, and in vitro assays. Results: Network pharmacology screening uncovered 46 overlapping targets between Astragalus root and DN. Protein-protein interaction (PPI) network analysis identified five core candidate targets: CASP3, VEGFA, CTNNB1, MYC, and PRKCB. KEGG pathway analysis indicated that the AGE-RAGE signaling pathway was the most significantly enriched. Molecular docking revealed that quercetin, β-carotene, daidzein, capsaicin, and kaempferol—major bioactive components of Astragalus root—bound strongly to each of the five core targets. Molecular dynamics simulations further confirmed the conformational stability of kaempferol when complexed with these target proteins. In vitro experiments showed that kaempferol markedly reduced protein levels of α-SMA, Col I, and Col IV; lowered secretion of TNF-α, IL-6, and IL-1β; and decreased ROS and MDA content. Additionally, kaempferol's therapeutic effects were mediated through suppression of the AGE-RAGE-PKC-TGF-β signaling axis. Conclusions: This work identified kaempferol, a bioactive ingredient of Astragalus root, as a potential therapeutic agent against DN, along with its target pathways. These findings provide a scientific foundation for its clinical translation.

Astragalus root, a traditional Chinese herbal remedy, has shown potential benefits against diabetic nephropathy (DN). However, the mechanisms driving its effects remain poorly understood. This study explored the molecular pathways through which Astragalus root improves DN. To identify possible targets and mechanisms of Astragalus root in DN treatment, we applied network pharmacology, molecular docking, molecular dynamics simulation, and in vitro assays. Network pharmacology screening uncovered 46 overlapping targets between Astragalus root and DN. Protein–protein interaction (PPI) network analysis identified five core candidate targets: CASP3, VEGFA, CTNNB1, MYC, and PRKCB (PKCβ). KEGG pathway analysis indicated that the AGE-RAGE signaling pathway was the most significantly enriched. Molecular docking revealed that quercetin, β-carotene, daidzein, capsaicin, and kaempferol—potential bioactive components of Astragalus root—bound strongly to each of the five core targets. Molecular dynamics simulations further confirmed the conformational stability of kaempferol when complexed with these target proteins. In vitro experiments showed that kaempferol markedly reduced protein levels of α-SMA, Col I, and Col IV; lowered secretion of TNF-α, IL-6, and IL-1β; and decreased ROS and MDA content. Additionally, kaempferol’s therapeutic effects were mediated through suppression of the AGE-RAGE-PKCβ-TGF-β1 signaling axis. This work identified kaempferol, a bioactive ingredient of Astragalus root, as a potential therapeutic agent against DN, along with its target pathways. These findings provide a scientific foundation for its clinical translation.

This study aims to screen and identify potential atherosclerosis (AS) biomarkers associated with common plasticizer exposure, providing a basis for future investigation into targeted therapeutic strategies. AS-related datasets (from public databases) and common plasticizers (ATBC, DEP, DMP, DOP) were used. First, plasticizer-related genes (PRGs) and AS-related genes (ASRGs) were ascertained from public databases, respectively. Biomarkers were then determined through differential expression, machine learning, receiver operating characteristic (ROC), and gene expression analyses. To further explore the biological mechanisms underlying AS, functional enrichment, immune infiltration, molecular docking, molecular dynamics (MD) simulations, and single-cell RNA sequencing (scRNA-seq) analyses were conducted. In this study, AR and CCR2 were recognized as biomarkers for AS, with AR showing significantly lower expression in AS samples and CCR2 demonstrating significantly higher expression. These biomarkers were co-enriched in the "cytokine-cytokine receptor interaction" pathway. Additionally, 5 immune cell types with differential infiltration were ascertained, with regulatory T cells showing a strong correlation with both biomarkers. Molecular docking revealed favorable binding between the biomarkers and ATBC, with a particularly moderate binding energy of -7.1 kcal/mol between CCR2 and ATBC. MD simulations confirmed the stability of the CCR2-ATBC complex. Finally, scRNA-seq analysis ascertained vascular smooth muscle cells (VSMCs) and T lymphocytes as key cell types in AS, with dynamic expression patterns of AR and CCR2 observed during their differentiation. Our study identifies AR and CCR2 as biomarkers linking plasticizer exposure to AS. These findings elucidate potential molecular mechanisms and offer promising directions for future experimental validation and therapeutic exploration.