Metabolic syndrome (MetS) is a worldwide condition that markedly elevates the risk of chronic conditions. The cholesterol, high-density lipoprotein, and glucose (CHG) indices simultaneously reflect various metabolic parameters, including lipid metabolism, cardiovascular function, and insulin sensitivity, providing considerable clinical value. This study aimed to investigate the association between the CHG index and MetS, along with their connections with all-cause death and cardiovascular disease (CVD) death in individuals with MetS. The NHANES dataset (2001–2018) was used to assess the relationship between the CHG index and MetS via cross-sectional research and weighted logistic regression analysis. Cohort studies and a weighted Cox proportional hazards model were employed to investigate the relationships of CHG with all-cause mortality and cardiovascular mortality in individuals with MetS. A possible nonlinear association between the CHG score and MetS, along with all-cause and CVD mortality in MetS patients, was assessed via general additive models and smooth fitting of curves. Kaplan‒Meier (K‒M) survival curves were generated to illustrate prognostic variations across CHG index quartiles. Subgroup analyses were performed to investigate discrepancies in these associations across different populations. Finally, the consistency and dependability of the outcomes were verified through repeated analysis via multiple imputation of the data and external validation with CHARLS. After adjusting for relevant confounding factors, the CHG index was positively correlated with all-cause Mortality and CVD Mortality among individuals with MetS. Further analysis revealed a U-shaped nonlinear relationship for these associations, with inflection points at 46.12, 52.67, and 50.82, respectively. K‒M survival curve analysis indicated that the prognosis for the middle quartile of the CHG index was better than that for both the lower and upper quartiles. Subgroup analyses further highlighted differences in these associations across various populations. Ultimately, the sensitivity analysis demonstrated the robustness of the findings. The CHG index has a substantial U-shaped nonlinear association with the incidence of MetS and the risk of all-cause and cardiovascular death in patients with MetS. Previous interventions have focused primarily on high-risk extremes, but the findings of this study suggest that patients with low CHG levels should also be included in monitoring. Future prospective studies are needed to validate these findings and explore their potential clinical applications in managing MetS patients.

Cancer immunotherapy represents a major breakthrough in oncology, particularly with immune checkpoint inhibitors (ICIs) and CAR-T cell therapies. Despite improved outcomes, challenges such as immune-related adverse events (irAEs) and treatment resistance limit clinical use. Artificial intelligence (AI) offers new opportunities to address these barriers, including target identification, efficacy prediction, toxicity monitoring, and personalized treatment design. This review highlights recent advances in AI applications for biomarker discovery, safety evaluation, gene editing, nanotechnology, and microbiome modulation, integrating evidence from clinical and preclinical studies. We also discuss future directions and challenges in applying AI to cancer immunotherapy, aiming to support further research and clinical translation.

PE is a life‐threatening pregnancy disorder that can lead to adverse events for both the fetus and the mother. Autophagy is a cellular process involved in cellular renovation and maintaining homeostasis. There is a growing body of evidence suggesting that autophagy in trophoblasts plays a significant role in the development and pathogenesis of PE. However, the exact mechanisms are not yet fully understood. This article provides an overview of recent evidence regarding the role of autophagy in trophoblast invasion, vascular remodelling, inflammation, immune response, and maternal factors in the context of PE. It is believed that impaired or excessive autophagy can contribute to placental ischaemia and hypoxia, thereby exacerbating PE progression. Therefore, understanding the molecular mechanisms that regulate autophagy in PE is crucial for the development of targeted therapeutic interventions in the future.

Background: Dietary antioxidants have been found to improve various diseases, including digestive, cardiovascular, and urinary disorders. However, the relationship between CDAI and constipation remains unclear. This study aims to investigate the potential link between CDAI and constipation among adults in the United States. Methods: This study utilized data from the National Health and Nutrition Examination Survey (NHANES) collected between 2005 and 2010. Dietary data from the respondents were obtained through two 24-hour dietary recall interviews. Multiple statistical methods, including multivariable logistic regression, subgroup analysis, and smooth curve fitting analysis, were used to explore the association between CDAI and chronic constipation. Results: A total of 10,904 participants were included in the study, of whom 1,184 were identified as having chronic constipation. After adjusting for potential confounders, multivariable logistic regression analysis showed that higher CDAI was significantly associated with a lower risk of constipation (OR = 0.958 [0.929, 0.987]). Compared to the lowest quartile, the highest quartile of CDAI was associated with a significantly reduced prevalence of constipation (OR = 0.704 [0.535, 0.927]). Subgroup analysis indicated that differences in gender, alcohol intake, and smoking status might influence the association between CDAI and constipation. Smooth curve analysis revealed an "n" shaped relationship between CDAI and constipation among non-alcohol consumers, with a turning point at a CDAI value of 1.08. Conclusion: An elevated CDAI is negatively correlated with the incidence of chronic constipation, suggesting that increasing dietary antioxidant intake may reduce constipation prevalence. These findings underscore the importance of dietary antioxidants in maintaining gut health and provide comprehensive guidance for clinical and public health practices.

Background: Frailty severely impacts patients’ quality of life and imposes a significant burden on healthcare systems. The Dietary Index for Gut Microbiota (DI-GM) is an emerging dietary indicator, and its association with frailty has not been thoroughly investigated.Methods: This study utilized data from NHANES 2007–2018 and assessed the association between DI-GM and frailty using multivariable weighted logistic regression, restricted cubic splines (RCS), subgroup analysis, and mediation analysis, after adjusting for relevant covariates.Results: The results indicate a significant negative correlation between DI-GM and frailty, with each standard unit increase in DI-GM reducing the risk of frailty by 6% (OR = 0.940 [0.899, 0.984]). DI-GM at different quartiles showed a strong dose–response relationship, with the highest quartile showing a 21.6% risk reduction. RCS analysis revealed a linear relationship between DI-GM and frailty. Subgroup analysis suggested that age and smoking status may influence the association between DI-GM and frailty. Furthermore, albumin and high-density lipoprotein (HDL) played significant mediating roles in the relationship between DI-GM and frailty, accounting for 30.34 and 9.05% of the total effect, respectively.Conclusion: Dietary Index for Gut Microbiota is negatively associated with frailty risk, and albumin and HDL mediate this association. Improving dietary quality may be an effective strategy for reducing frailty risk.

Introduction Breast and colorectal cancer are a major global public health problem. Breast cancer is one of the most common cancers worldwide. Colorectal cancer is the third most common cancer and the second most common cause of tumor death worldwide. Central memory T (TCM) cells are closely related to the development of tumors and important targets for immunotherapy. Therefore, identifying the common signaling molecules of these two diseases in TCM cells can improve our understanding of these diseases and lead to the development of therapies that can be effective for treating both. Methods Single-cell RNA (scRNA) data of breast cancer (GSE161529) and colorectal cancer (GSE222300) patients was downloaded from the GEO database. The data were normalized and dimension reduced, then different T cell subsets were identified and differential gene expression analysis of central memory CD8 + T cells was conducted. Mendelian randomization analysis, reverse causality detection, and co-localization analysis was performed to explore the relationship between differentially-expressed genes and the disease. Quasi-temporal analysis and metabolic analysis was done using scRNA sequencing technology and further analysis of gene expression and metabolism in spatial transcriptomes. Finally, the degree of association between drug target genes was analyzed by protein-protein interaction (PPI) analysis. Results Our analysis identified four genes (ZFP36L2, CKS1B, PTTG1, and ITGAE) that were associated with risk of both breast and colorectal cancer. In the pseudotime analysis, we found that the expression levels of CKS1B and PTTG1 decreased over time (p < 0.05) while ZFP36L2 and ITGAE increased over time (p < 0.05). In the metabolic analysis, these four genes were closely associated with the cysteine and methionine metabolism pathways, which was corroborated in the spatial transcription analysis. Finally, the PPI analysis among the drug target genes identified an interaction between PTTG1 and CKS1B genes. Conclusion This study reports that the ZFP36L2, CKS1B, PTTG1, and ITGAE genes could potentially influence breast cancer and colorectal cancer development via TCM CD8 + T cells. These four genes are putative common markers for diagnosis, treatment, and monitoring tumor response to therapies.