Nangarhar University

Variation in litter size (LS) in sheep is linked to genetic factors, including the Zona pellucida-3 (ZP3) gene, which plays a role in ovine reproductive processes. This study examined the association between ZP3 gene variations and LS in Kari sheep. Two groups of 160 Kari ewes were analysed: one consistently producing singletons and another producing twins, with occasional triplets. Additionally, Madakhlasht sheep, which sometimes produce twins, and Balkhi sheep, which produce only singletons, were used as references. The entire ZP3 gene was amplified using PCR and sequenced at 30× with Next Generation Sequencing. Bioinformatics analysis identified 70 variants across the three breeds, located in upstream regions, introns, and exons. Notably, two point mutations and a six-nucleotide insertion were found upstream of the initiation codon in twin-producing Kari ewes, potentially affecting ZP3 expression and LS. Two missense mutations (I101L in exon 1 and R408H in exon 8) were heterozygous in twin-producing Kari ewes but homozygous in other groups, correlating with LS. Protein modelling suggested that the I101L mutation alters the binding site, potentially impacting protein function. These findings indicate that ZP3 gene variations influence reproductive efficiency and LS in sheep, with specific variants serving as potential markers for selective breeding to enhance LS.

This study examined the effects of dietary supplementation with animal protein concentrate (APC) and ginger phyto-protease (GPZ) on growth performance, carcase yield, litter quality and gut microbiota in broiler chicks over a 35-day period.A total of 700-day-old chicks were divided into give groups with five replicates as follow: control (standard diet), diet with 4% APC, diet with 6% APC, diet with 4% APC+GPZ at 0.02% and diet with 6% APC+GPZ at 0.02%.The results showed that GPZ supplementation improved body weight gain (BWG) and feed conversion ratio (FCR) in diets containing APC.Carcase yield anal. revealed that diet with 4% APC+GPZ, and diet with 6% APC+GPZ had the highest yields (p< 0.01).Immune organ weights of spleen and bursa of fabricius were significantly increased in groups having 4 and 6% APC with GPZ (p= 0.02).Addnl., gut microbiota anal. indicated that treatments with GPZ effectively reduced harmful bacteria (Clostridium perfringens, Escherichia coli, and Salmonella) while promoting the growth of beneficial Lactobacillus.Overall, GPZ supplementation at the level of 0.02% in 4% APC added diet proved more effective in improving feed conversion, reducing harmful bacteria, and promoting the growth of beneficial gut microbiota.

The role of carbon dioxide as a green alternative solvent has garnered significant interest for its application in various industrial processes, including chem. reactions, separations, and material processing.Polyethylene glycol (PEG) is a valuable compound with extensive applications in industries such as pharmaceuticals, biotechnol., and chem. engineering.Precise estimation of viscosity of CO2-saturated PEG is crucial for several scientific and industrial applications, as viscosity directly impacts the material′s performance and feasibility in specific processes.This study, hence, introduces machine learning models utilizing K-nearest neighbors, decision tree, adaptive boosting, multilayer perceptron artificial neural network, convolutional neural network, support vector machine, random forest and ensemble learning algorithms to accurately forecast the dynamic viscosity of CO2-saturated PEG based on PEG molar mass, pressure, and temperatureAn exptl. dataset is employed to facilitate the development of these intelligent models.Addnl., the leverage method is utilized to assess the authenticity of the data for model development, while a relevancy index is used to elucidate the relative contributions of each input factor to the viscosity.The findings suggest that all the collected exptl. data are appropriate for inclusion in the construction of data-driven models.Moreover, it is revealed that pressure, temperature and PEG molar mass have a neg. effect on the viscosity of CO2-saturated PEG.Ultimately, multilayer perceptron artificial neural network model is found to be the most accurate method for predicting CO2-saturated PEG viscosity.