Bioactivity of Juglans regia kernel extracts optimized using response surface method and artificial neural Network-Genetic algorithm integration

利用响应面法和人工神经网络-遗传算法相结合的方法优化胡桃核提取物的生物活性

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Abstract

In this study, the biological activities of the extracts obtained under optimum extraction conditions of the kernel part of Juglans regia L. were determined. Two different methods, Response Surface Method (RSM) and Artificial Neural Network-Genetic Algorithm (ANN-GA) integration, were used for optimization. The antioxidant capacity of the extracts obtained under the extract conditions suggested by the two methods was evaluated by Rel Assay kits, DPPH and FRAP methods. Anticholinesterase activities of the optimized extracts were measured by the action of acetylcholinesterase and butyrylcholinesterase enzymes. Antiproliferative effects of the extracts were tested on A549 lung cancer cell line. Phenolic compounds were analyzed by LC-MS/MS. It was determined that both extracts exhibited strong activities against A549 lung cancer cell line depending on the concentration increase. In addition, it was determined that both extracts exhibited acetyl and butyrylcholinesterase inhibition activity close to galantamine used as a standard. In both extracts, 13 compounds including gallic acid, catechinhyrate, 4-hydroxybenzoic acid, caffeic acid, vanillic acid, syringic acid, 2-hydoxycinamic acid, resveratrol, myricetin, quercetin, kaempferol, protocatechuic acid and 2-hyroxy1,4 naphthaquinone were identified. It was determined that the extract obtained under the conditions predicted by ANN-GA exhibited higher activities in general.

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