{"title":"利用响应面法和人工神经网络遗传算法对核桃核提取物的生物活性进行优化。","authors":"Ayşenur Gürgen","doi":"10.1038/s41598-025-93499-z","DOIUrl":null,"url":null,"abstract":"<p><p>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.</p>","PeriodicalId":21811,"journal":{"name":"Scientific Reports","volume":"15 1","pages":"8981"},"PeriodicalIF":3.9000,"publicationDate":"2025-03-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11910572/pdf/","citationCount":"0","resultStr":"{\"title\":\"Bioactivity of Juglans regia kernel extracts optimized using response surface method and artificial neural Network-Genetic algorithm integration.\",\"authors\":\"Ayşenur Gürgen\",\"doi\":\"10.1038/s41598-025-93499-z\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>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.</p>\",\"PeriodicalId\":21811,\"journal\":{\"name\":\"Scientific Reports\",\"volume\":\"15 1\",\"pages\":\"8981\"},\"PeriodicalIF\":3.9000,\"publicationDate\":\"2025-03-15\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11910572/pdf/\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Scientific Reports\",\"FirstCategoryId\":\"103\",\"ListUrlMain\":\"https://doi.org/10.1038/s41598-025-93499-z\",\"RegionNum\":2,\"RegionCategory\":\"综合性期刊\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"MULTIDISCIPLINARY SCIENCES\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Scientific Reports","FirstCategoryId":"103","ListUrlMain":"https://doi.org/10.1038/s41598-025-93499-z","RegionNum":2,"RegionCategory":"综合性期刊","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"MULTIDISCIPLINARY SCIENCES","Score":null,"Total":0}
Bioactivity of Juglans regia kernel extracts optimized using response surface method and artificial neural Network-Genetic algorithm integration.
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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