Impact of linear alkyl benzene sulphonate (LAS) on phosphatase activity in testis of the teleostean fish,Heteropneustes fossilis (Bloch)

Fishes are sensitive indicators of pollutants present in water.These pollutants cause various physical and physiological alterations in fishes. In the present work alteration in the activity of acid and alkaline phosphatase was evaluated in testicular tissue of fresh water fish Heteropneustes fossilis exposed to LC50 value of linear alkyl benzene sulphonate (LAS) for different exposure periods [24 h, 48 h, 72 h and 96 h] With increase in the concentration of chemical LAS, the activity of acid phosphatase (ACP) was reported elevated while a significant fall in the activity of alkaline phosphatase (ACP) was recorded for same exposure period. Elevated activity of ACP, one of the important hydrolases of lysosomes, is quite suggestive of bringing about gross necrosis and dysarchitecture. ALP is involved in various metabolic activities including gonadal maturation and as such decreased activity of this enzyme is definitely one of the important causative factors for reproductive impairment of the fish.     

Mechanistic insights to lactic and formic acid toxicity on benthic oligochaete worm Tubifex tubifex

Environmental Science and Pollution Research - Lactic and formic acid are two commonly found monocarboxylic organic acids. Lactic acid is discharged into the water bodies as acidic industrial...     

Performance assessment of the indigenous ceramic UF membrane in bioreactor process for highly polluted tannery wastewater treatment

Environmental Science and Pollution Research - The present study evaluates the performance of an indigenously developed ceramic ultrafiltration (UF) membrane in a lab-scale membrane bioreactor...     

Enhancement of nutritional value of fried fish using an artificial intelligence approach

Frying affects the nutritional quality of fish detrimentally. In this study, using Catla catla and mustard oil, experiments were carried out in varying temperatures (140–240 °C), times (5–20 min), and oil amounts (25–100 ml/kg of fish) which established drastic reduction of 44.97% and 99.40% for polyunsaturated fatty acid (PUFA)/saturated fatty acids (SFA) and index of atherogenicity (IA) profile, respectively. Artificial neural network (ANN) was implemented successfully to provide an association between the independent inputs with dependent outputs (values of R² were 0.99 and 0.98; RMSE were 0.038 and 0.046; and performance were 0.038 and 0.067 for PUFA/SFA and IA, respectively) by exhaustive search of various algorithms and activation functions available in literature. ANN model–based meta-heuristic, stochastic optimization formalisms, genetic algorithm (GA) and particle swarm optimization (PSO), were applied to optimize the combination of cooking parameters for improving the nutritional quality of food which improved the nutritional value by maximizing the PUFA/SFA profile up to 63.05% and minimizing the IA profile to 99.64%. Multi-objective genetic algorithm (MOGA) was also employed to tune the inputs by maintaining a balance between the contrasting outputs and enhance the overall food value simultaneously with multi-objective (beneficial for health, economic, and environment-friendly) proposal. MOGA was able to improve the PUFA/SFA profile up to 44.76% and reduce the IA profile to 92.94% concurrently with the reduction of wastage of culinary media and energy consumption, following the optimized cooking condition (118.92 °C, 6.06 min, 40 ml oil/kg of fish).