Effects of supplementary inulin on ewes milk composition and rumen fermentation parameters.

This experiment aimed to investigate the effects of inulin supplementation on milk production and composition, feed intake, nutrient digestibility and rumen fermentation parameters in lactating ewes. The experimental treatments were (1) control group (basal diet), (2) basal diet plus 2% inulin (w/w) and (3) basal diet plus 4% inulin (w/w). The experiment was carried out for 21 d in a fully randomized design involving eighteen Ghezel ewes. Production and composition (percentages of fat, protein, lactose and fat-free solids and fatty acid profiles) of milk were measured. Faeces were collected in the last 3 days of the experiment to determine digestibility. On the last day of the experiment, rumen fluid samples were taken from the esophagus 3 h after feeding and fermentation parameters (pH, ammonia nitrogen (N-NH3), volatile fatty acids (VFA) and protozoal population) were examined. Daily milk production was not significantly affected by inulin supplementation, but the fat and protein content of the milk was increased whilst urea nitrogen (MUN) and unsaturated fatty acids were decreased (P < 0.05). The dry matter (DM) intake results showed that there was no significant difference between different diets. The highest digestibility of DM and NDF belonged to the inulin fed group (P < 0.05). Inulin consumption numerically increased the pH of the rumen fluid of the animals and significantly decreased the rumen N-NH3 value (P < 0.05). Inulin supplementation also significantly increased total VFA, acetate, and butyrate levels (P < 0.05). In general, it can be concluded that inulin supplementation can improve rumen fermentation, DM and NDF digestibility,as well as compositional aspects of the ewe's milk production.

Analysis of gene expression profiles and protein-protein interaction networks in multiple tissues of systemic sclerosis.

BACKGROUND: Systemic sclerosis (SSc), a multi-organ disorder, is characterized by vascular abnormalities, dysregulation of the immune system, and fibrosis. The mechanisms underlying tissue pathology in SSc have not been entirely understood. This study intended to investigate the common and tissue-specific pathways involved in different tissues of SSc patients. METHODS: An integrative gene expression analysis of ten independent microarray datasets of three tissues was conducted to identify differentially expressed genes (DEGs). DEGs were mapped to the search tool for retrieval of interacting genes (STRING) to acquire protein-protein interaction (PPI) networks. Then, functional clusters in PPI networks were determined. Enrichr, a gene list enrichment analysis tool, was utilized for the functional enrichment of clusters. RESULTS: A total of 12, 2, and 4 functional clusters from 619, 52, and 119 DEGs were determined in the lung, peripheral blood mononuclear cell (PBMC), and skin tissues, respectively. Analysis revealed that the tumor necrosis factor (TNF) signaling pathway was enriched significantly in the three investigated tissues as a common pathway. In addition, clusters associated with inflammation and immunity were common in the three investigated tissues. However, clusters related to the fibrosis process were common in lung and skin tissues. CONCLUSIONS: Analysis indicated that there were common pathological clusters that contributed to the pathogenesis of SSc in different tissues. Moreover, it seems that the common pathways in distinct tissues stem from a diverse set of genes.

CatbNet: A Multi Network Analyzer for Comparing and Analyzing the Topology of Biological Networks.

BACKGROUND: Complexity and dynamicity of biological events is a reason to use comprehen-sive and holistic approaches to deal with their difficulty. Currently with advances in omics data genera-tion, network-based approaches are used frequently in different areas of computational biology and bio-informatics to solve problems in a systematic way. Also, there are many applications and tools for net-work data analysis and manipulation which their goal is to facilitate the way of improving our under-standings of inter/intra cellular interactions. METHODS: In this article, we introduce CatbNet, a multi network analyzer application which is prepared for network comparison objectives. RESULT AND CONCLUSION: CatbNet uses many topological features of networks to compare their structure and foundations. One of the most prominent properties of this application is classified network analysis in which groups of networks are compared with each other.