Annamalai University

About: Annamalai University is a education organization based out in Chidambaram, Tamil Nadu, India. It is known for research contribution in the topics: Lipid peroxidation & Antioxidant. The organization has 8098 authors who have published 10758 publications receiving 203872 citations.

Ellagic acid coordinately attenuates Wnt/β-catenin and NF-κB signaling pathways to induce intrinsic apoptosis in an animal model of oral oncogenesis

Abstract: Constitutive activation of the Wnt signaling pathway and its downstream effectors plays a key role in neoplastic transformation. The objective of this study was to investigate the effect of ellagic acid, a plant-derived polyphenol on Wnt/β-catenin signaling and its downstream circuits- NF-κB and mitochondrial apoptosis in the 7,12-dimethylbenz[a]anthracene (DMBA)-induced hamster buccal pouch (HBP) carcinogenesis model. Hamsters were divided into six groups. The right buccal pouches of animals in groups 1–4 were painted with 0.5% DMBA three times a week for 14 weeks. Animals in groups 2–4 received in addition basal diet containing ellagic acid at a concentration of 0.1, 0.2, and 0.4% in the diet. Group 5 animals were given 0.4% ellagic acid alone. Group 6 animals served as control. The expression of the members of Wnt and NF-κB signaling and intrinsic apoptosis was evaluated by western blot analysis. Dietary supplementation of 0.4% ellagic acid suppressed the development of HBP carcinomas by preventing the constitutive activation of Wnt pathway through the downregulation of Fz, Dvl-2, GSK-3β and nuclear translocation of β-catenin. Abrogation of Wnt signaling by ellagic acid was also associated with inactivation of NF-κB and modulation of key components of the mitochondrial apoptotic network. Our findings suggest a functional crosstalk between Wnt and NF-κB signaling pathways in HBP carcinomas that is blocked by ellagic acid supplementation. Dietary ellagic acid that targets the Wnt/β-catenin pathway as well as its downstream signaling mediators is a unique candidate for cancer chemoprevention.

Antioxidant and antihyperlipidemic effect of Solanum nigrum fruit extract on the experimental model against chronic ethanol toxicity

Abstract: The possible protective effect of Solanum nigrum fruit extract (SNFEt) was investigated for its antioxidant and antihyperlipidemic activity against ethanol-induced toxicity in rats. The experimental animals were intoxicated with 20% ethanol (7.9 g/kg/day) for 30 days via gastric intubation. SNFEt was administered at the dose of 250 mg/kg body weight along with the daily dose of ethanol for 30 days. From the result it was observed that ethanol-induced rats showed a significant elevation in the levels of Thiobarbituric acid reactive substances (TBARS), which lowered the antioxidant defense systems, such as, reduced glutathione (GSH) and vitamins C and E, when compared to the controls. In the lipid profiles, the levels of total cholesterol (TC), triglycerides (TG), low density lipoproteins (LDL), very low density lipoproteins (VLDL), free fatty acids (FFA), and phospholipids were significantly elevated in the ethanol-induced group, whereas, the high density lipoproteins (HDL) were found to be reduced in the plasma, and the phospholipid levels were significantly decreased in the tissues. Supplementation of SNFEt improved the antioxidant status by decreasing the levels of TBARS and altering the lipid profiles to near normal. These activities were also compared to the standard drug silymarin (25 mg/ kg body weight). Thus the findings of the present study indicated a significant antioxidant and antihyperlipidemic activity of Solanum nigrum fruits, which offered protection against ethanol-induced toxicity.

Parametric optimization for floating drum anaerobic bio-digester using Response Surface Methodology and Artificial Neural Network

Abstract: The main purpose of this study to increase the optimal conditions for biogas yield from anaerobic digestion of agricultural waste (Rice Straw) using Response Surface Methodology (RSM) and Artificial Neural Network (ANN). In the development of predictive models temperature, pH, substrate concentration and agitation time are conceived as model variables. The experimental results show that the liner model terms of temperature, substrate concentration and pH, agitation time have significance of interactive effects (p < 0.05). The results manifest that the optimum process parameters affected on biogas yield increase from the ANN model when compared to RSM model. The ANN model indicates that it is much more accurate and reckons the values of maximum biogas yield when compared to RSM model.