This study was carried out to evaluate the hepato-protective property of (Arachis hypogea L.) peanut skin extracts in CCl4 induced hepatotoxicity in mice. The antioxidant activity was measured utilizing 2, 2-diphenyl-1-1 picrylhydrazyl (DPPH) radical scavenging capacity. The results showed that the methanolic extract was the highest free radical scavenging activity than the aqueous extract with values (92.34 ± 0.45 and 87.62 ± 0.44) respectively in 12 mg/mL compared to 89.61 ± 0.34 for Butylated hydroxytoluene (BHT) and 93.25 ± 0.06 for vitamin C, which means that the methanolic extract of peanut skin is superior to BHT. Furthermore, the total phenolic content was analyzed by using Folin-Ciocalteu method, the amount of total phenol in aqueous extract was15.32 ± 0.45, 39.29 ± 0.64 and 56.63 ± 1.03 mg/g in 2, 6 and 10 mg/ml respectively, while the methanolic extract was 47.08 ± 0.56, 68.40 ± 1.18 and 85.35 ± 0.62 mg/g respectively in the same concentrations. The hepato-protective effect of peanut skin extract was evaluated in CCl4 induced hepato-toxicity. The experiment was conducted in two methods: pre-treatment groups and post-treatment groups. Mice were treated with 50 and 100 mg/kg of aqueous and methanolic peanut skin extracts for 35 days before being damaged by CCl4 (pre-treatment group), and the other groups (post-treatment groups) which the mice were injected with CCl4 and received 50 and 100 mg/kg of aqueous and methanolic peanut skin extracts for 35 days. Biochemical studies show that there is decrease in the levels of serum ALT, AST, ALP, MDA and increases in the levels of SOD with significant differences (p <0.01) when compared with the CCl4 treated group. The histo pathological examination of liver obtained from mice with administrated intraperitoneally 3 ml/kg CCl4 showed histopathological changes in the liver represented in fatty changes of excessive hepatocyte accumulation of fatty material, while when treated with 100 mg/kg of peanut extract revealed look like normal structure appearance of hepatic tissue and normal structure appearance but with few apoptotic cells.
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Background: The world is in front of two emerging problems being scarceness of virgin re-sources for bioactive materials and the gathering of waste production. Employment of the surplus waste in the mainstream production can resolve these problems. The current study aimed to prepare and characterize a natural composite CaO-SiO2 based bioactive material derived from naturally sustained raw materials. Then deposit this innovative novel bioactive coating composite materials overlying Yttria-stabilized tetragonal zirconia substrate. Mate-rials and method; Hen eggshell-derived calcium carbonate and rice husk-derived silica were extracted from natural resources to prepare the composite coating material. The manufac-tured powder was characterized
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Ag-doped NiO thin films were fabricated by dip coating and subsequently annealed at 373, 473, 573, and 673 K to elucidate the influence of annealing temperature on their structural, morphological, optical, and NO2-sensing characteristics. X-ray diffraction confirmed the formation of polycrystalline Ag/NiO films, with progressively improved crystallinity and larger crystallite size at elevated annealing temperatures. Atomic force microscopy revealed a homogeneous surface morphology with grain growth, with the average grain diameter increasing from 26.40 to 34.2 nm. Optical analysis showed high visible-region transmittance (65–70%) and a gradual reduction in the optical band gap from 2.75 to 2.07 eV with increasing annealing temperature. Ga
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To evaluate the shear bond strength and interfacial morphology of sound and caries-affected dentin (CAD) bonded to two resin-modified glass ionomer cements (RMGICs) after 24 hours and two months of storage in simulated body fluid at 37°C.
Sixty-four permanent human mandibular first molars (32 sound and 32 with occlusal caries, following the International Caries Detection and Assessment System) were selected. Each prepared substrate (sound and CAD) was co
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Advanced strategies for production forecasting, operational optimization, and decision-making enhancement have been employed through reservoir management and machine learning (ML) techniques. A hybrid model is established to predict future gas output in a gas reservoir through historical production data, including reservoir pressure, cumulative gas production, and cumulative water production for 67 months. The procedure starts with data preprocessing and applies seasonal exponential smoothing (SES) to capture seasonality and trends in production data, while an Artificial Neural Network (ANN) captures complicated spatiotemporal connections. The history replication in the models is quantified for accuracy through metric keys such as m
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Hydrate dissociation equilibrium conditions for carbon dioxide + methane with water, nitrogen + methane with water and carbon dioxide + nitrogen with water were measured using cryogenic sapphire cell. Measurements were performed in the temperature range of 275.75 K–293.95 K and for pressures ranging from 5 MPa to 25 MPa. The resulting data indicate that as the carbon dioxide concentration is increased in the gas mixture, the gas hydrate equilibrium temperature increases. In contrast, by increasing the nitrogen concentration in the gas mixtures containing methane or carbon dioxide decreased the gas hydrate equilibrium temperatures. Furthermore, the cage occupancies for the carbon dioxide + methane system were evaluated using the Van der Wa
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