Effects of replacing soybean meal with pumpkin seed cake and dried distillers grains with solubles on milk performance and antioxidant functions in dairy cows

Pumpkin seed cake (PSC), a byproduct of pumpkin seed oil processing, is used in ruminant feed as a beneficial protein source. Experiments were conducted to evaluate PSC as a substitute for soybean meal in the diets of lactating cows based on performance, rumen fermentation, antioxidant function and nitrogen partitioning. Six multiparous lactating cows were used in a replicated 3 × 3 Latin square experiment with 27-day periods. The cows were randomly divided into three treatment groups: group (1) was fed a diet containing no PSC (0PSC), and groups (2) and (3) were fed diets in which soybean meal was replaced with PSC and dried distillers grains with solubles (DDGS) at levels of 50% (50PSC) and 100% (100PSC), respectively. The diets were isonitrogenous and contained identical roughage but different proportions of PSC and DDGS. Replacement of soybean meal with PSC and DDGS did not influence rumen degradation, milk performance, rumen fermentation, DM intake or apparent total tract digestibility, and nitrogen partitioning between milk, feces and urine did not differ in the animals fed the three diets. However, compared with a diet containing no PSC, the total antioxidant capacity (P < 0.05) and antioxidant enzymes (total superoxide dismutase, glutathione peroxidase and catalase) activities (P < 0.05) were increased in the animals that received the 50PSC and 100PSC diets. In contrast, addition of PSC significantly reduced concentrations of aspartate transaminase (P < 0.05), alkaline phosphatase (P < 0.05) and malondialdehyde (P < 0.05) in the plasma. These results demonstrate that PSC can be completely substituted for soybean meal in the diet of dairy cows without any negative impact on milk performance, rumen fermentation or apparent digestibility and that this dietary change improves antioxidant functions and blood parameters in dairy cows, indicating that PSC has the potential for use as a feed source for dairy cows.

Prioritizing candidate disease miRNAs by topological features in the miRNA target-dysregulated network: case study of prostate cancer

Recently, microRNAs (miRNA), small noncoding RNAs, have taken center stage in the field of human molecular oncology. However, their roles in tumor biology remain largely unknown. According to the assumption that miRNAs implicated in a specific tumor phenotype will show aberrant regulation of their target genes, we introduce an approach based on the miRNA target-dysregulated network (MTDN) to prioritize novel disease miRNAs. Target genes have predicted binding sites for any miRNA. The MTDN is constructed by combining computational target prediction with miRNA and mRNA expression profiles in tumor and nontumor tissues. Application of the proposed method to prostate cancer reveals that known prostate cancer miRNAs are characterized by a greater number of dysregulations and coregulators and the tendency to coregulate with each other and that they share a higher proportion of targets with other prostate cancer miRNAs. Support vector machine classifier, based on these features and changes in miRNA expression, is constructed and gives an average overall prediction accuracy of 0.8872 in cross-validation tests. The classifier is then applied to miRNAs in the MTDN. Functions enriched by dysregulated targets of novel predicted miRNAs are closely associated with oncogenesis. In addition, predicted cancer miRNAs within families or from different families show combinatorial dysregulation of target genes, as revealed by analysis of the MTDN modular organization. Finally, 3 miRNA target regulations are verified to hold in prostate cancer cells by transfection assays. These results show that the network-centric method could prioritize novel disease miRNAs and model how oncogenic lesions are mediated by miRNAs, providing important insights into tumorigenesis.

MiRNA-miRNA synergistic network: construction via co-regulating functional modules and disease miRNA topological features

Synergistic regulations among multiple microRNAs (miRNAs) are important to understand the mechanisms of complex post-transcriptional regulations in humans. Complex diseases are affected by several miRNAs rather than a single miRNA. So, it is a challenge to identify miRNA synergism and thereby further determine miRNA functions at a system-wide level and investigate disease miRNA features in the miRNA–miRNA synergistic network from a new view. Here, we constructed a miRNA–miRNA functional synergistic network (MFSN) via co-regulating functional modules that have three features: common targets of corresponding miRNA pairs, enriched in the same gene ontology category and close proximity in the protein interaction network. Predicted miRNA synergism is validated by significantly high co-expression of functional modules and significantly negative regulation to functional modules. We found that the MFSN exhibits a scale free, small world and modular architecture. Furthermore, the topological features of disease miRNAs in the MFSN are distinct from non-disease miRNAs. They have more synergism, indicating their higher complexity of functions and are the global central cores of the MFSN. In addition, miRNAs associated with the same disease are close to each other. The structure of the MFSN and the features of disease miRNAs are validated to be robust using different miRNA target data sets.