Splenic gene expression profiling in White Leghorn layer inoculated with the Salmonella enterica serovar Enteritidis

Salmonella enterica serovar Enteritidis (SE) is a foodborne pathogen that can threaten human health through contaminated poultry products. Live poultry, chicken eggs and meat are primary sources of human salmonellosis. To understand the genetic resistance of egg‐type chickens in response to SE inoculation, global gene expression in the spleen of 20‐week‐old White Leghorn was measured using the Agilent 4 × 44 K chicken microarray at 7 and 14 days following SE inoculation (dpi). Results showed that there were 1363 genes significantly differentially expressed between inoculated and non‐inoculated groups at 7 dpi (I7/N7), of which 682 were up‐regulated and 681 were down‐regulated genes. By contrast, 688 differentially expressed genes were observed at 14 dpi (I14/N14), of which 371 were up‐regulated genes and 317 were down‐regulated genes. There were 33 and 28 immune‐related genes significantly differentially expressed in the comparisons of I7/N7 and I14/N14 respectively. Functional annotation revealed that several Gene Ontology (GO) terms related to immunity were significantly enriched between the inoculated and non‐inoculated groups at 14 dpi but not at 7 dpi, despite a similar number of immune‐related genes identified between I7/N7 and I14/N14. The immune response to SE inoculation changes with different time points following SE inoculation. The complicated interaction between the immune system and metabolism contributes to the immune responses to SE inoculation of egg‐type chickens at 14 dpi at the onset of lay. GC, TNFSF8, CD86, CD274, BLB1 and BLB2 play important roles in response to SE inoculation. The results from this study will deepen the current understanding of the genetic response of the egg‐type chicken to SE inoculation at the onset of egg laying.     

中药联合微生态制剂防治呼吸、消化系统病毒病

本文阐述了中药防治病毒病的历史及其应用概况,中药联合微生态制剂防治呼吸、消化系统病毒病的理论依据、临床应用和发展前景。     

基于指标自动筛选的新疆开孔河流域生态健康评价

生态健康评价对了解区域生态健康状况和促进区域可持续发展具有重要意义,如何自动筛选出能反映生态系统特性的重要指标,是生态健康定量评估的关键问题。基于压力-状态-响应(PSR,Press-State-Response)框架和生态等级网络框架(EHN,Ecological Hierarchy Network),通过文献调研和因果分析建立要素层与指标层之间的交叉联系,构建了生态健康评价"网状"指标体系;在保证指标体系完备性基础上,通过结合主成分分析和熵权法的候选指标权重的客观计算,基于目标优化理论构建了评价指标的自动筛选模型,并基于中选指标计算了新疆开孔河流域2001—2017年生态健康指数(EHCI,Ecological Health Comprehensive Indexes),分析其空间分异和时间变化特征。结果表明:利用所建立的评价指标自动筛选模型,开孔河流域生态健康评价指标由31个候选指标自动筛选出了17个中选指标,用54.8%的指标表达了85.98%的信息,中选的17个指标在干旱/半干旱区域有关文献中应用较多,使用频次比例都在20%以上,其中归一化植被指数(NDVI,Normalized Difference Vegetation Index)、年降水量和植被覆盖度(FVC,Fractional Vegetation Coverage)3个指标的使用频次百分比均超过了50%,说明指标自动筛选模型的合理性;开孔河流域空间分布差异显著,总体上西北高、东南低,东南部和中部绿洲区外围生态健康状况较差,西北部河谷地带和中部两大绿洲区生态健康状况较好;17年来,流域生态质量整体趋于改善,显著改善区域占10.26%,远高于显著退化的1.61%,显著改善区域以孔雀河绿洲最为明显。开孔河流域生态健康的总体好转趋势说明区域生态综合治理取得一定成效。