Propolis is a resinous substance produced by honey bees that is very popular as a natural remedy in traditional medicine. The current research is the first study on the biological properties of ethanolic extracts of propolis (EEP) from several different regions (12) of Iran. Total phenolic and flavonoid contents (TPC and TFC) of Iranian EEPs were variable between 26.59-221.38 mg GAE/g EEP and 4.8-100.03 mg QE/g EEP. The DPPH scavenging assay showed all the studied EEP samples, except for the sample with the lowest TPC and TFC (P6), have suitable antioxidant activity. All the EEPs inhibited both cholinesterase enzymes (acetylcholinesterase: AChE, butyrylcholinesterase: BuChE) but most of them exhibited a distinct selectivity over BuChE.Evaluation of the antibacterial activity of the EEP samples using four pathogenic bacteria (B. cereus, S. aureus, A. baumannii, and P. aeruginosa) demonstrated that the antibacterial properties of propolis are more effective on the gram-positive bacterium.Spearman correlation analysis showed a strong positive correlation between TPC and TFC of the Iranian EEPs and their antioxidant, anticholinesterase, and antibacterial activities. Considering that there is ample evidence of anticholinesterase activity of flavonoids and a significant correlation between the anticholinesterase activity of the studied Iranian EEPs and their total flavonoid content was observed, the interaction of 17 well-known propolis flavonoids with AChE and BuChE was explored using molecular docking. The results indicated that all the flavonoids interact with the active site gorge of both enzymes with high affinity. Summing up, the obtained results suggest that Iranian propolis possesses great potential for further studies.

Background Artificial and natural selection for important economic traits and genetic adaptation of the populations to specific environments have led to the changes on the sheep genome. Recent advances in genome sequencing methods have made it possible to use comparative genomics tools to identify genes under selection for traits of economic interest in domestic animals. Objectives In this study, we compared the genomes of Assaf and Awassi sheep breeds with those of the Cambridge, Romanov and British du cher sheep breeds to explore positive selection signatures for milk traits using nucleotide diversity (Pi) and FST statistical methods. Methods Genome sequences from fourteen sheep with a mean sequence depth of 9.32X per sample were analysed, and a total of 23 million single nucleotide polymorphisms (SNPs) were called and applied for this study. Genomic clustering of breeds was identified using ADMIXTURE software. The FST and Pi values for each SNP were computed between population A (Assaf and Awassi) and population B (Cambridge, British du cher, and Romanov). Results The results of the PCA grouped two classes for these five dairy sheep breeds. The selection signatures analysis displayed 735 and 515 genes from FST and nucleotide diversity (Pi) statistical methods, respectively. Among all these, 12 genes were shared between the two approaches. The most conspicuous genes were related to milk traits, including ST3GAL1 (the synthesis of oligosacáridos), CSN1S1 (milk protein), CSN2 (milk protein), OSBPL8 (fatty acid traits), SLC35A3 (milk fat and protein percentage), VPS13B (total milk production, fat yield, and protein yield), DPY19L1 (peak yield), CCDC152 (lactation persistency and somatic cell count), NT5DC1 (lactation persistency), P4HTM (test day protein), CYTH4 (FAT Production) and METRNL (somatic cell), U1 (milk traits), U6 (milk traits) and 5S_RRNA (milk traits). Conclusions The findings provide new insight into the genetic basis of sheep milk properties and can play a role in designing sheep breeding programs incorporating genomic information.

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Proper primer design is actually one of the most important factors/steps in successful DNA sequencing. There are many constraints that should be satisfied for designing the optimal primers. In recent years, many methods have been proposed to provide feasible primer set. But designed primer sets by these methods usually do not provide a specific PCR product. Moreover, this process takes a long time. Today, for obtaining approved solutions, evolutionary Algorithms have been applied to the primer design problem. This paper presents a primer design method based on Gravitational Search Algorithm (GSA). GSA is a recently proposed optimization algorithm that is applied for many problems. For valid comparison, the gene CYP1A has been selected that is frequently used in previous researches. This gene is associated with a heightened lung cancer risk. Analyzing of the results confirms that the accuracy, time efficiency and reliability of GSA based method are better than PSO based method.