Effects of Astragalus membranaceus Polysaccharides on Growth Performance, Physiological and Biochemical Parameters, and Expression of Genes Related to Lipid Metabolism of Spotted Sea Bass, Lateolabrax maculatus

This experiment investigated the effects of Astragalus membranaceus polysaccharides (AMP) on growth, physiological and biochemical parameters, and the expression of lipid metabolism-related genes in spotted sea bass, Lateolabrax maculatus. A total of 450 spotted sea bass (10.44±0.09 g) were divided into six groups and were given diets with different levels of AMP (0, 0.2, 0.4, 0.6, 0.8, and 1.0 g/kg) for 28 days, respectively. Results indicated that dietary intake of AMP significantly improved fish weight gain, specific growth rate, feed conversion, and trypsin activity. Meanwhile, fish fed with AMP manifested significantly higher serum total antioxidant capacity and activity of hepatic superoxide dismutase, catalase, and lysozyme. Lower triglyceride and total cholesterol were noted in fish fed with AMP (P<0.05). Moreover, hepatic ACC1 and ACC2 were downregulated by dietary intake of AMP, and PPAR-α, CPT1, and HSL were upregulated accordingly (P<0.05). Parameters with significant difference were analyzed by quadratic regression analysis, and results showed that 0.6881 g/kg of AMP is the optimal dosage for spotted sea bass in size (10.44±0.09 g). In conclusion, dietary intake of AMP can improve the growth, physiological status, and lipid metabolism of spotted sea bass, thereby indicating its promise as a potential dietary supplement

Genomic insights and prognostic significance of novel biomarkers in pancreatic ductal adenocarcinoma: A comprehensive analysis

Pancreatic ductal adenocarcinoma (PDAC) is a highly prevalent digestive system malignancy, with a significant impact on public health, especially in the elderly population. The advent of the Human Genome Project has opened new avenues for precision medicine, allowing researchers to explore genetic markers and molecular targets for cancer diagnosis and treatment. Despite significant advances in genomic research, early diagnosis of pancreatic cancer remains elusive due to the lack of highly sensitive and specific markers. Therefore, there is a need for in-depth research to identify more precise and reliable diagnostic markers for pancreatic cancer. In this study, we utilized a combination of public databases from different sources to meticulously screen genes associated with prognosis in pancreatic cancer. We used gene differential analysis, univariate cox regression analysis, least absolute selection and shrinkage operator (LASSO) regression, and multivariate cox regression analysis to identify genes associated with prognosis. Subsequently, we constructed a scoring system, validated its validity using survival analysis and ROC analysis, and further confirmed its reliability by nomogram and decision curve analysis (DCA). We evaluated the diagnostic value of this scoring system for pancreatic cancer prognosis and validated the function of the genes using single cell data analysis. Our analysis identifies six genes, including GABRA3, IL20RB, CDK1, GPR87, TTYH3, and KCNA2, that were strongly associated with PDAC prognosis. Clinical prognostic models based on these genes showed strong predictive power not only in the training set but also in external datasets. Functional enrichment analysis revealed significant differences between high- and low-risk groups mainly in immune-related functions. Additionally, we explored the potential of the risk score as a marker for immunotherapy response and identified key factors within the tumor microenvironment. The single-cell RNA sequencing analysis further enriched our understanding of cell clusters and six hub genes expressions. This comprehensive investigation provides valuable insights into pancreatic PDAC and its intricate immune landscape. The identified genes and their functional significance underscore the importance of continued research into improving diagnosis and treatment strategies for PDAC