Microencapsulated herbal components in the diet of Lacaune ewes: impacts on physiology and milk production and quality

Abstract This study aimed to determine whether the addition of a microencapsulated herbal blend (MHB) based on thymol, carvacrol, and cinnamaldehyde in dairy sheep feed would improve production efficiency, milk quality, and animal health. Thirty lactating Lacaune ewes were divided into three groups: Control (T0), 150 mg blend/kg of feed (T150), and 250 mg blend/kg of feed (T250). Milk was measured before the beginning of the experiment (d 0), at the end of the adaptation period (d 15), and during the experiment (d 20). In milk samples, was measured the composition, somatic cell count (SCC), reactive oxygen species (ROS), lipoperoxidation (LPO), and total antioxidant capacity. The MHB improved the milk production (only T150 vs. T0 sheep on d 20), productive efficiency and feed efficiency, and reduced the milk SCC (only T250 vs. T0 sheep, on d 20), ROS and tended to reduce the milk levels of LPO (only T250 vs. T0 sheep on d 20). Also, MHB reduced the blood levels of neutrophils and ROS (only T250 vs. T0 sheep on d 20) and increased total protein and globulin levels. Thus, a microencapsulated blend of thymol, carvacrol, and cinnamaldehyde improved the productive performance and milk quality of sheep

Network Analysis Tools: from biological networks to clusters and pathways

Network Analysis Tools (NeAT) is a suite of computer tools that integrate various algorithms for the analysis of biological networks: comparison between graphs, between clusters, or between graphs and clusters; network randomization; analysis of degree distribution; network-based clustering and path finding. The tools are interconnected to enable a stepwise analysis of the network through a complete analytical workflow. In this protocol, we present a typical case of utilization, where the tasks above are combined to decipher a protein–protein interaction network retrieved from the STRING database. The results returned by NeAT are typically subnetworks, networks enriched with additional information (i.e., clusters or paths) or tables displaying statistics. Typical networks comprising several thousands of nodes and arcs can be analyzed within a few minutes. The complete protocol can be read and executed in B1 h