Manizheh Tehrani; Abdulghaffar Ownagh
Volume 14, Issue 6 , June 2023, , Pages 317-322
Abstract
Q fever is a worldwide zoonosis caused by an obligate intra-cellular pathogen called Coxiella burnetii affecting a broad range of animal hosts including horses. Most of the isolates found carry plasmids which genetic studies of C. burnetii strains suggest a critical role in C. burnetii survival. The ...
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Q fever is a worldwide zoonosis caused by an obligate intra-cellular pathogen called Coxiella burnetii affecting a broad range of animal hosts including horses. Most of the isolates found carry plasmids which genetic studies of C. burnetii strains suggest a critical role in C. burnetii survival. The correlation between an isolated plasmid type and the chronic or acute nature of the disease has always been controversial. This study was conducted to investigate the prevalence of C. burnetii QpH1 and QpDG plasmids in horses and assess the potential role of these species as reservoirs of infection and transmission. Nested-polymerase chain reaction (PCR) assays were performed on 320 blood serum samples drawn from horses in West Azerbaijan province, Iran, in 2020. In total, 26 (8.13%) Q fever-positive samples based on containing the IS1111 gene were tested by nested-PCR approach to amplify QpH1 and QpDG plasmid segments. The QpH1 and QpRS plasmid-specific sequences were identified in 19 (73.07%) and none in the serum samples, respectively. According to the present study, the age of the animal can be considered as an important risk factor for the prevalence of C. burnetii; but, the season, sex, and breed of the horse had no effect on the prevalence of disease. The results indicate that nested-PCR method could be suitable for routine diagnosis, to gather new information about the shedding of C. burnetii, and to improve the knowledge of contamination routes.
Rahim Peyghan; Ala Enayati; Mostafa Sabzevarizadeh
Volume 4, Issue 3 , September 2013, , Pages 175-178
Abstract
Thyroid hormones (T3, T4) have marked effect on body metabolism and in controlling osmoregulation activity in fish. The aim of this study was to determine the effect of water salinity changes on thyroid hormones level and thyroid-stimulating hormone (TSH) of grass carp. For this purpose 120 grass carp ...
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Thyroid hormones (T3, T4) have marked effect on body metabolism and in controlling osmoregulation activity in fish. The aim of this study was to determine the effect of water salinity changes on thyroid hormones level and thyroid-stimulating hormone (TSH) of grass carp. For this purpose 120 grass carp were divided randomly in to four groups (10 fish in each group and three replicates per treatment). Three groups were held in three different salinities at concentrations of 4, 8 and 12 g L-1. The fourth group was reared in fresh water and considered as control. After three weeks blood samples were collected from the caudal peduncle vein. Then serum was separated and serum thyroid hormones and TSH were measured by LISA on Microwell plates. Our results indicated that the average of T3 levels in 4, 8 and 12 g L-1 groups were 0.43 ± 0.11, 0.22 ± 0.04 and 0.21 ± 0.04 μg dL-1, respectively. T3 levels in all experimental groups were significantly lower than those of control group (p < 0.05). Serum T4 level in 4, 8 and 12 g L-1 groups were 0.29 ± 62955/40.06, 0.24 ± 43129/50.05 and 2.85 7958/± 05768/40.55 μg dL-1, respectively. Thyroxine level was significantly higher only in 12 g L-1 group in comparison with the control and other experimental groups (p < 0.05). Thyroxine level in other groups had not any significant difference with the control group (p > 0.05). The level of TSH in salinities of 4 and 8 g L-1 groups was significantly higher than that of control group (p < 0.05). The results showed that increasing water salinity can have significant effect on thyroid activity by decreasing T3 and increasing T4 level in serum of grass carp in experimental condition.
Shahram Nozad; Ali-Gholi Ramin; Gholamali Moghadam; Siamak Asri-Rezaei; Azadeh Babapour; Sina Ramin
Volume 3, Issue 1 , March 2012, , Pages 55-59
Abstract
Seventy six high and low producer cows were selected to determine the composition of the blood and milk parameters, and their interrelationships to determine the indices which could be useful to improve the milk yield. The highest mean blood concentrations were found in high producer cows. Mean values ...
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Seventy six high and low producer cows were selected to determine the composition of the blood and milk parameters, and their interrelationships to determine the indices which could be useful to improve the milk yield. The highest mean blood concentrations were found in high producer cows. Mean values for blood urea nitrogen (BUN), serum protein (SPtn), creatinine, triglycerides (TGs), cholesterol, and beta-hydroxybutyric acid (BHB) were 25.10 mg dL-1, 10.15 g dL-1, 0.81, 62.30, 177.10 and 0.16 mmol L-1, and for macro-minerals including SCa, SMg, serum in-organic phosphorus (SIP), SNa and SK were 3.85, 2.66, 4.63, 108.00 and 4.34 mmol L-1, respectively. The highest concentrations for milk parameters, were observed in the high producers, and were significant only for MCa, MIP and MMg. Mean values for milk urea nitrogen (MUN), milk protein (MPtn) and lactose were 19.90 mg dL-1, 0.39 g dL-1, and 4.12% and for macro-minerals, 13.24, 3.88, 11.03, 73.30 and 16.90 mmol L-1, respectively. There were significant positive correlations between the blood and milk parameters except for creatinine/BHB, TGs/cholesterol and MNa/MK which were not significant. The correlations between the blood parameters were greater than in the milk parameters. Creatinine and SPtn, MUN and MPtn were the main parameters in that the relationships between MPtn with BUN, SPtn and creatinine were more noticeable than others. The regression analysis showed that BUN with the SIP and creatinine, MPtn with the BUN and creatinine and MUN with the SIP and SMg were the appropriate parameters in improvement studies related to the milk yield. In conclusion, BUN, SPtn, MUN and MPtn concentrations are the most effective indices for predicting the preferred milk yield.
