Purpose: To evaluate the effect of oral magnesium sulfate (MgSO) on the gene expression and serum levels of inflammatory cytokines including TNF-α, IL-18, IL-1β, IL-6, and IFN-γ in patients with moderate coronary artery disease (CAD).
Methods: 60 CAD patients were selected based on angiography findings and were randomly divided into two groups that received 300 mg/day MgSO (n = 30) or placebo (n = 30) for 3 months. Gene expression and serum levels of inflammatory cytokines were assessed.
Results: After 3 months of intervention, gene expression and serum levels of IL-18 and TNF-α in the MgSOgroup were significantly less than the placebo group (P < 0.05). However, no significant difference in gene expression and serum levels of IL-1β, IL-6, and IFN-γ was observed between the two groups (P > 0.05). In addition, within group analysis demonstrate that Mg-treatment significantly decrease serum level of TNF-α and IL-18 as compared to pretreatment.
Conclusion: The results of our study demonstrate that 3-month magnesium sulfate administration (300 mg/day) to CAD patients could significantly decrease serum concentration and gene expression levels of IL-18 and TNF-α. Our findings support the potential beneficial effect of magnesium supplementation on alleviating CAD complications through modulating inflammatory cytokines.
It is now understood that brain metastases do not occur randomly but have distinct spatial patterns depending on the origin of the cancer. According to the "seed and soil" hypothesis, the final colonization of metastatic cells is the result of their adaptation to the altered environment. To investigate the most favorable microenvironment for brain metastasis, we analyzed neuroimaging data from 177 patients with breast cancer brain metastasis and 548 patients with lung cancer brain metastasis to create a replicable probabilistic map of metastatic locations.
Introduction: Typhoid fever is an infectious disease primarily caused by sv. Typhi ( Typhi), a bacterium that causes as many as 20 million infections and 600,000 deaths annually. Asymptomatic chronic carriers of S.
Background: Asthma is a global chronic respiratory disease with complex pathogenesis. While current therapies offer some relief, they often fall short in effectively managing symptoms and preventing exacerbations for numerous patients. Thus, understanding its mechanisms and discovering new drug targets remains a pressing need for better treatment.
This paper develops a method for cancer classification from microRNA data using a convolutional neural network (CNN)-based model optimized by genetic algorithm. The convolutional neural network has performed well in various recognition and perception tasks. This paper contributes to the cancer classification using a union of two CNNs.
Department of Otolaryngology, Longgang Otolaryngology hospital & Shenzhen Key Laboratory of Otolaryngology, Shenzhen Institute of Otolaryngology, Shenzhen, Guangdong, China.
Head and neck squamous carcinoma (HNSC), characterized by a high degree of malignancy, develops in close association with the tumor immune microenvironment (TIME). Therefore, identifying effective targets related to HNSC and TIME is of paramount importance. Here, we employed the ESTIMATE algorithm to compute immune and stromal cell scores for HNSC samples from the TCGA database and identified differentially expressed genes (DEGs) based on these scores.
