The present study aims to examine the relationships between temperature and humidity and milk composition, microbial load, and somatic cells in the milk of Holstein dairy cows. For this purpose, the temperature–humidity index, ambient temperature, and relative humidity data were obtained from the nearest weather stations. Production data were obtained from four dairy farms in Golestan province, Iran, collected from 2016 to 2021. The traits investigated were protein, fat, solids-not-fat (SNF), microbial load, and somatic cell count (SCC) in milk. The effects of the environmental temperature, humidity, month, and season on the milk composition, microbial load, and somatic cells were analyzed through analysis of variance. The effects of environmental temperature, humidity, month, and season on the milk composition, microbial load, and somatic cell composition were analyzed using a mixed procedure with a restricted maximum likelihood model. Although our findings revealed that there were significant differences in fat, protein, SNF, and SCC among the different months of the year (p < 0.01), no significant difference was observed in the total microbial count in milk. Environmental temperature presented significant impacts on fat, protein, SNF, SCC, and total microbial count within various temperature ranges (p < 0.01). When the temperature increased from 6.2 °C to 31.3 °C, the milk protein, fat, SNF, and somatic cell count significantly decreased, by approximately 4.09%, 5.75%, 1.31%, and 16.8%, respectively; meanwhile, the microbial count in milk significantly increased, by approximately 13.7%. Humidity showed an influence on fat, protein, non-fat solids, somatic cells, and total microbial count within different temperature ranges (p < 0.01). When the humidity increased from 54% to 82%, the milk protein, fat, SNF, and SCC significantly increased, by approximately 3.61%, 4.84%, 1.06%, and 10.2%, respectively; meanwhile, the microbial count in milk significantly decreased, by approximately 16.3%. The results demonstrate that there is a negative correlation between different months of the year, temperature, and the humidity of the environment, in terms of milk components and SCC. Our findings demonstrate that the optimum performance, in terms of milk composition, occurred in the first quarter of the year. As temperature increases and humidity decreases, milk quality decreases. Therefore, the adverse effects of environmental conditions on agricultural profits are not negligible, and strategies to better deal with the negative environmental effects are needed in order to improve milk quality in dairy cows.

The present study was carried out to estimate variance components for growth traits in Naeini goats. Bodyweight records were collected for two flocks under supervision of the Agriculture Organisation of the Esfahan province between 2000 and 2007. Investigated traits were birthweight (BW; n = 2483), weaning weight (WW; n = 1211) and average daily gain from birth to weaning (ADG; n = 1211). Environmental effects were investigated using fixed-effect models, while (co)variance components and genetic parameters were estimated with single- and three-trait analyses using REML methods and WOMBAT software. Six different animal models were fitted to the traits, with the best model for each trait determined by log-likelihood ratio tests (LRT). All traits were significantly influenced by herd, birth year, sex of the kid, birth type and dam age (P < 0.01). On the basis of LRT, maternal permanent environmental effects (c2) were significant for WW and ADG, while BW was affected only by direct genetic effects. Direct heritability estimates for BW, WW and ADG were 0.25 ± 0.05, 0.07 ± 0.06 and 0.21 ± 0.11, respectively. The estimate of c2 was 0.16 ± 0.06 for both WW and ADG. Estimates of genetic correlation for BW–ADG, BW–WW and ADG–WW were 0.49, 0.61 and 0.94, respectively. The estimated phenotypic correlations were positive and were between 0.03 (BW–ADG) and 0.95 (ADG–WW). These results indicate that selection can be used to improve growth traits in this goat breed.

Due to the unique affinity of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) to the angiotensin-converting enzyme 2 (ACE2) receptor in patients, the foremost recent evidence indicated that ACE1 and ACE2 polymorphisms could affect the susceptibility of individuals to SARS-CoV-2 infection and also the disease outcome. Here, we aimed to assess the possible association between two polymorphisms and the severity of disease in patients. In the present study, 146 patients with COVID-19 who were admitted to the Mazandaran University of Medical Sciences hospitals between March 2020 and July 2020 were enrolled in this case–control study. The patients were divided into four groups based on clinical symptoms and severity of the diseases (mild, moderate, severe, and critical). After DNA extraction, the ACE gene I/D polymorphism (rs4646994) and ACE2 gene polymorphism (rs2285666) were genotyped using Gap-PCR and PCR–RFLP techniques, respectively. Then, five samples from each obtained genotype were confirmed by Sanger sequencing technique. Data were analyzed with SAS software version 9.1 using appropriate statistical procedures. The ACE gene I/D polymorphism (rs4646994) genotypes were classified into three types: I/I, I/D, and D/D. Our finding indicated that the prevalence of ACE1 D/D genotype was significantly higher in severe and critical COVID-19 patients (P = 0.0016). Additionally, the analysis revealed a remarkable association between rs4646994 SNP and the HB and ESRI levels in patients (P < 0.05). Although the ACE2 rs2285666 SNP was not related to the severity of disease, this variant was significantly associated with ALT, ESRI, and P. These results provide preliminary evidence of a genetic association between the ACE-D/D genotype and the D allele of ACE1 genotype and the disease severity. Therefore, our findings might be useful for identifying the susceptible population groups for COVID-19 therapy.

Increased lipid peroxidation and decreased antioxidant status can result in reduced reproductive activity and fertility in aged male broiler breeders. This study was conducted to evaluate the effects of curcumin supplements (natural or nanoparticles) on the sperm characteristics, antioxidant system, fertility, and hatchability of aged roosters (54-64 wk), and to estimate the relative bioavailability value (RBV) of nano-curcumin on the measured parameters including the hypo-osmotic swelling test (HOST), motility, viability, sperm count, volume, the concentration of testosterone, glutathione peroxidase (GPx), and superoxide dismutase (SOD), diameter of the spermatogenic tube (DST), epithelium thickness (Epi_Th), spermatogonia count (SP_count), fertility, hatchability, and relative weight of testis (RW-testis). A total of 30 roosters were individually caged and randomly assigned to 5 treatments comprising control (without curcumin as the basal diet), basal diet + 15 mg/kg curcumin (CUR15), basal diet + 30 mg/kg curcumin (CUR30), basal diet + 15 mg/kg nano-curcumin (Nano15), and basal diet + 30 mg/kg nano-curcumin (Nano30) for 10 wk. The slope ratio method was used to estimate the bioavailability of nano-curcumin by regressing each response on supplemental curcumin intake. Increasing dietary curcumin (P < 0.001) elicited a linear response to all studied traits. The RBV for volume, viability, motility, HOST, RW-testis, and GPx were estimated as 135 (CI: 115-156%), 143 (CI: 114-173%), 159 (CI: 122-196%), 132 (CI: 107-157%), 195 (CI: 126-264%), 176 (CI: 103-249%), and 178% (28-328%), respectively. Our findings revealed that curcumin nanoparticles enhance the reproductive efficiency of aged breeder roosters. In addition, the curcumin nanoparticles RBV exceeded that of natural curcumin, suggesting that lower concentrations of curcumin nanoparticles could have a significant effect on reproductive characteristics.