The present study aimed to investigate the acetamiprid effects on biochemical aspects in albino mice. Thirty albino mice at the age of 6-8 weeks and average weight 25±5 g were divided into three groups each having ten (10) healthy mice. The first group was orally administrated with distilled water while the second and third groups were orally administrated with 50 mg/mL and 100 mg/mL respectively of acetamprid (0.1 mL) daily for one week. LD50 of acetamiprid was measured and found to be 200 mg/kg. The parameters of evaluations included liver function using Aspartate Aminotransferase (AST), Alanine Aminotransferase (ALT) and Alkaline Phosphatase (ALP). Lipid profile was analysed using Total Cholesterol (TC), Triglycerides (TG), High Density Lipoprotein (HDL), Low Density Lipoprotein (LDL) and Very Low Density Lipoprotein (VLDL). Antioxidant factors such as Superoxide Dismutase (SOD), Malondialdehyde (MDA), Catalase (CAT) and Glutathione Peroxidase (GPx), Calcium ion (ca2+ ) and Aacetylcholine Esterase (AchE) were also measured. The study suggested that acetamprid 100 mg\mL significantly affected the biochemical component and it was considered to be a toxic dose of acetamiprid in albino mice.
The objective of this review was to describe the COVID-19 complications after recovery.
The researchers systematically reviewed studies that reported post-COVID-19 complications from three databases: PubMed, Google Scholar and the World Health Organization (WHO) COVID-19 database. The search was conducted between 21 November 2020 and 14 January 2021. Inclusion criteria were articles written in English, with primary data, reporting complications of COVID-19 after full
Receipt date: 8/8/2020 acceptance date: 9/11/2020 Publication date: 31/12/2021
This work is licensed under a Creative Commons Attribution 4.0 International License.
The American-Iranian relations have been characterized by tensions since the arrival of the guardian jurist regime in Iran to leadership in 1979, as it was considered a turning point not only in the cont
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The objective of this study was to develop neural network algorithm, (Multilayer Perceptron), based correlations for the prediction overall volumetric mass-transfer coefficient (kLa), in slurry bubble column for gas-liquid-solid systems. The Multilayer Perceptron is a novel technique based on the feature generation approach using back propagation neural network. Measurements of overall volumetric mass transfer coefficient were made with the air - Water, air - Glycerin and air - Alcohol systems as the liquid phase in bubble column of 0.15 m diameter. For operation with gas velocity in the range 0-20 cm/sec, the overall volumetric mass transfer coefficient was found to decrease w
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