Temporal trend in burden of asthma in China, South Korea, and Japan, 1990-2019: results from the Global Burden of Disease Study 2019.

Background: Asthma is a public health problem worldwide. However, only a few studies have reported the epidemiology of asthma in various age groups in East Asia. The present study aimed to analyze and predict trends in the incidence of asthma in East Asia through the Global Burden of Disease 2019 (GBD 2019) study and provide information for prevention and control strategies. Methods: The estimates of incidence, deaths, disability-adjusted life years (DALYs), and risk factors of asthma in China, South Korea, Japan, and the world from 1990-2019 were retrieved from the GBD 2019 study. The age-standardized rates (ASRs) and the average annual percentage changes (AAPCs) assessed the incidence, deaths, and DALYs of asthma, and the projection was assessed by applying the age-period-cohort model. Results: The burden of asthma in South Korea and Japan was slightly higher than in China and slightly lower than that worldwide. The age-standardized incidence rate (ASIR) of asthma in China decreased slightly from 394.58/100,000 in 1990 to 355.33/100,000 in 2019 (with an AAPC of -0.59), while the age-standardized death rate (ASDR) and the age-standardized DALY rate (ASDALR) decreased significantly (with a AAPCs of -5.22 and -2.89, respectively), which were lower than those in South Korea and Japan. Moreover, males in China, South Korea, and Japan were significantly more affected by tobacco and environmental/occupational factors than females, while the proportion of metabolic factors in females was higher than that in males. The prediction for the burden of asthma in the three East Asian countries continued to decline or stabilize until 2030, especially in China and Japan. Conclusions: Although the overall asthma burden has a downward trend according to GBD 2019, it is still heavy in East Asia, especially South Korea. In addition, increased concern and control measures are needed for the disease burden in elderly patients.

Identification of immune-related gene signature for predicting prognosis in uterine corpus endometrial carcinoma.

The objective of this study is to develop a gene signature related to the immune system that can be used to create personalized immunotherapy for Uterine Corpus Endometrial Carcinoma (UCEC). To classify the UCEC samples into different immune clusters, we utilized consensus clustering analysis. Additionally, immune correlation algorithms were employed to investigate the tumor immune microenvironment (TIME) in diverse clusters. To explore the biological function, we conducted GSEA analysis. Next, we developed a Nomogram by integrating a prognostic model with clinical features. Finally, we performed experimental validation in vitro to verify our prognostic risk model. In our study, we classified UCEC patients into three clusters using consensus clustering. We hypothesized that cluster C1 represents the immune inflammation type, cluster C2 represents the immune rejection type, and cluster C3 represents the immune desert type. The hub genes identified in the training cohort were primarily enriched in the MAPK signaling pathway, as well as the PD-L1 expression and PD-1 checkpoint pathway in cancer, all of which are immune-related pathways. Cluster C1 may be a more suitable for immunotherapy. The prognostic risk model showed a strong predictive ability. Our constructed risk model demonstrated a high level of accuracy in predicting the prognosis of UCEC, while also effectively reflecting the state of TIME.

Network pharmacology and experimental verification based research into the effect and mechanism of Aucklandiae Radix-Amomi Fructus against gastric cancer.

To investigate the mechanism of the Aucklandiae Radix-Amomi Fructus (AR-AF) herb pair in treating gastric cancer (GC) by using network pharmacology and experimental verification. Using the traditional Chinese medicine system pharmacology database and analysis platform (TCMSP), the major active components and their corresponding targets were estimated and screened out. Using Cytoscape 3.7.2 software, a visual network was established using the active components of AR-AF and the targets of GC. Based on STRING online database, the protein interaction network of vital targets was built and analyzed. With the Database for Annotation, Visualization, and Integrated Discovery (DAVID) server, the gene ontology (GO) biological processes and the Kyoto Encyclopedia of Genes and Genomes (KEGG) signaling pathways of the target enrichment were performed. AutoDock Vina was used to perform molecular docking and calculate the binding affinity. The mRNA and protein expression levels of the hub targets were analyzed by the Oncomine, GEPIA, HPA databases and TIMER online tool, and the predicted targets were verified by qRT-PCR in vitro. Eremanthin, cynaropicrin, and aceteugenol were identified as vital active compounds, and AKT1, MAPK3, IL6, MAPK1, as well as EGFR were considered as the major targets. These targets exerted therapeutic effects on GC by regulating the cAMP signaling pathway, and PI3K-Akt signaling pathway. Molecular docking revealed that these active compounds and targets showed good binding interactions. The validation in different databases showed that most of the results were consistent with this paper. The experimental results confirmed that eremanthin could inhibit the proliferation of AGS by reducing the mRNA expression of hub targets. As predicted by network pharmacology and validated by the experimental results, AR-AF exerts antitumor effects through multiple components, targets, and pathways, thereby providing novel ideas and clues for the development of preparations and the treatment of GC.