Background: Limited research has compared external beam radiotherapy (RT) to non-RT in patients with nonsurgical locally advanced pancreatic cancer (LAPC). Therefore, this study investigates the impact of RT on overall survival (OS) in patients with nonsurgical LAPC in a real-world context. Methods: The authors conducted an analysis of patients with nonsurgical LAPC using data from the Surveillance, Epidemiology, and End Results (SEER) database. This analysis involved the utilization of Kaplan–Meier survival curves and multivariable Cox regression analyses. Results: A total of 5413 individuals with nonsurgical LAPC were included in this analysis. Among them, 2320 (42.9%) received RT, while 3093 (57.1%) underwent non-RT treatment. The median OS was 12.0 months for the RT group and 9.0 months for the non-RT group, with a statistically significant difference ( P <0.001). Multivariate analysis revealed that RT had a statistically significant impact on OS (HR, 0.86; 95% CI: 0.81–0.91; P <0.001). Propensity score matching analysis confirmed a statistically significant association of RT with improved OS (HR, 0.84, 95% CI: 0.79–0.90; P <0.001). These results remained consistent after conducting sensitivity analyses, subgroup analyses, and propensity score matching. Conclusion: The study findings suggest that RT could be advantageous for patients with nonsurgical LAPC. Further investigations are warranted to explore the relationship between RT and OS.

The role of programmed cell death ligand 1 (PD-L1) in suppressing antitumor immune responses has been widely reported, and recent studies showed that PD-L1 also plays an important role in epithelial-mesenchymal transition (EMT), determination of tumor cell phenotypes, metastasis, and drug resistance. Long non-coding RNAs (lncRNAs) are involved in a variety of epigenetic regulatory processes. The tumorigenesis and development of most cancers cannot be studied separately from their regulation by lncRNAs. To explore the epigenetic regulation of PD-L1, we identified an lncRNA, LINC00244, which reduced PD-L1 expression and predicted good clinical outcomes in hepatocellular carcinoma (HCC). LINC00244 inhibited the proliferation, invasion, and metastasis of HCC by downregulating PD-L1 expression. In addition, low LINC00244 expression activated epithelial-mesenchymal transition (EMT) pathways and facilitated the rapid growth and metastasis of HCC cells. Thus, LINC00244 is a potential therapeutic target for HCC. Graphical abstract

Japanese encephalitis (JE) is a mosquito‐borne infectious disease that is primarily endemic in Asia and the Western Pacific region. In recent years, the epidemiological profile of JE in China has undergone significant transformations, posing novel challenges to disease control and prevention. To systematically evaluate these changes, we analyzed nationwide longitudinal surveillance data on JE incidence from 2004 to 2020. Bayesian spatiotemporal hierarchy model and age–period–cohort analysis were employed to explore long‐term trends and transmission dynamics, and the geographical detector model was used to assess the synergistic effects of meteorological, ecological, and socioeconomic factors on the distribution of JE. During the study period, a total of 43,857 JE cases were reported in mainland China, with an incidence rate per 100,000 population declining from 0.42 to 0.02. Spatially, traditional hyperendemic areas remained concentrated in southwest (Sichuan, Guizhou, Yunnan, and Chongqing), while significant northward expansion was observed in the northwestern China of Gansu and Shaanxi provinces. Our models indicated that spatiotemporal heterogeneity in JE transmission was strongly influenced by the interaction effects between socioeconomic development and meteorological variables, particularly the medical level, GDP per capita, and education level. These findings underscore the need for spatially adaptive and age‐specific public health strategies in response to changing JE risks under socioeconomic and environmental transitions.

Background: The influence of pyroptosis on tumors is complex and diverse. However, its specific impact on hepatocellular carcinoma (HCC) is still not well understood. Therefore, the objective of this study was to develop a prognostic signature for HCC based on pyroptosis-related genes. Methods: The single-cell RNA sequencing (scRNA-seq) data, mRNA expression files and corresponding clinical information of HCC were obtained from the The Cancer Genome Atlas and Gene Expression Omnibus databases. Python was used to process scRNA-seq data and calculated the enrichment score of pyroptosis-related genes (PRGs). Weight Co-Expression Network Analysis was used to identify pyroptosis-related hub genes. By overlapping the PRGs from scRNA-seq analysis and bulk RNA-seq analysis, respectively. Then, Univariate cox and LASSO regression were used to construct the pyroptosis prognostic model. Multivariate cox was used to identify independent factors for HCC and then developed a nomogram. The biological functions, survival analysis, immune characteristics, therapy response, and m6A modification status were analyzed. Results: Based on the scRNA-seq analysis and bulk RNA-seq analysis, hub PRGs were identified in HCC. Of those genes, five PRGs (ADGRE2, FCER1G, SLC9A9, CYBB, SLAMF6) were selected as a prognostic signature. The risk score established from the prognostic signature was an independent prognostic factor for HCC. The high-risk score group is associated with a poor prognosis, characterized by immunosuppressive features. Conclusion: This study uniquely integrates single-cell and bulk transcriptomic data to systematically identify pyroptosis-related prognostic biomarkers, pinpointing their cellular origin within the tumor microenvironment.

With global ageing accelerating, cognitive impairment has emerged as a critical public health challenge. Although vegetarian diets are often promoted for their health benefits, their specific impact on cognitive function in older adults remains scientifically controversial and insufficiently studied, particularly across diverse populations. This multi-national study analyzed data from China, Europe and the United States. Using logistic regression and mixed-effects models, we examined graded vegetarian diets' association with cognitive impairment in older adults, adjusting for key covariates. Findings were validated through sensitivity analyses and cross-cohort verification. Both lacto-ovo vegetarian (28% higher risk) and vegan (33% higher risk) diets showed significantly increased cognitive impairment risk compared to omnivorous diets. A pronounced gradient effect was observed, with stricter vegetarian diets associated with greater risk. This association was particularly strong in rural populations. Validation analyses confirmed these patterns in European cohorts and showed consistent trends in U.S. Strict vegetarian diets are associated with elevated cognitive impairment risk in older adults, especially in rural areas. These findings highlight the need for careful consideration of dietary patterns in ageing populations and suggest that less restrictive vegetarian diets may be preferable for cognitive health.

The glioma tumor microenvironment (TME) exhibits profound heterogeneity that drives tumor progression and therapy resistance. By integrating single-cell RNA sequencing (eleven samples) and spatial transcriptomics (two samples), the cellular components of the glioma microenvironment were deconvoluted, revealing tumor-associated foam cells (TAFCs) as the most abundant and centrally connected subtype. The high expression of two prognostic candidate genes, growth differentiation factor 8 (GDF-8, also known as myostatin, MSTN) and transcription factor 12 (TCF12), in TAFCs was found to be correlated with poor overall survival. These two genes were associated with M2 macrophage infiltration, altered cholesterol homeostasis, and immunosuppressive signaling. Regulatory network and pathway analyses, based on computational motif enrichment and co-expression analysis, linked them to ribosome, Notch signaling, DNA repair, and cell-cycle pathways. Pseudotime trajectories revealed dynamic expression during differentiation. Additionally, drug sensitivity prediction analysis demonstrated that MSTN expression was significantly associated with sensitivity to paclitaxel and VE-822, while TCF12 expression showed potential associations with sensitivity to cytarabine, olaparib, Wee1 inhibitor, paclitaxel, and VE-822. Logistic regression analysis combining clinical parameters with MSTN and TCF12 expression effectively achieved risk stratification for glioma, with higher composite scores predicting worse 2- and 3-year survival outcomes. Calibration curves demonstrated high consistency between nomogram-predicted overall survival probabilities and actual observed outcomes. Immunofluorescence confirmed upregulated expression of MSTN and TCF12 in glioma tissues and their co-localization with macrophages. In conclusion, this study identified TAFCs as the central cells in the glioma microenvironment, with their signature genes MSTN and TCF12 representing candidate immunometabolic signatures associated with macrophage-mediated immunosuppression and metabolic reprogramming in glioma, suggesting their potential as biomarkers for patient stratification and as targets for immunometabolic therapies.