Biological activities of Hypericum spectabile extract optimized using artificial neural network combined with genetic algorithm application.

IF 3.5 3区 生物学 Q2 BIOTECHNOLOGY & APPLIED MICROBIOLOGY
Ayşenur Gürgen, Mustafa Sevindik, Tetiana Krupodorova, Imran Uysal, Orhan Unal
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引用次数: 0

Abstract

Optimizing extraction conditions can help maximize the efficiency and yield of the extraction process while minimizing negative impacts on the environment and human health. For the purpose of the current study, an artificial neural network (ANN) combined with a genetic algorithm (GA) was utilized for that the extraction conditions of Hypericum spectabile were optimized. In this particular investigation, the main objective was to get the highest possible levels of total antioxidant status (TAS) for the extracts that were obtained. In addition to this, conditions of the extract that exhibited the maximum activity have been determined and the biological activity of the extract that was obtained under these conditions was analyzed. TAS values were obtained from extracts obtained using extraction temperatures of 30-60 °C, extraction times of 4-10 h, and extract concentrations of 0.25-2 mg/mL. The best model selected from the established ANN models had a mean absolute percentage error (MAPE) value of 0.643%, a mean squared error (MSE) value of 0.004, and a correlation coefficient (R) value of 0.996, respectively. The genetic algorithm proposed optimal extraction conditions of an extraction temperature of 59.391 °C, an extraction time of 8.841 h, and an extraction concentration of 1.951 mg/mL. It was concluded that the integration of ANN-GA can successfully be used to optimize extraction parameters of Hypericum spectabile. The total antioxidant value of the extract obtained under optimum conditions was determined as 9.306 ± 0.080 mmol/L, total oxidant value as 13.065 ± 0.112 µmol/L, oxidative stress index as 0.140 ± 0.001. Total phenolic content (TPC) was 109.34 ± 1.29 mg/g, total flavonoid content (TFC) was measured as 148.34 ± 1.48 mg/g. Anti-AChE value was determined as 30.68 ± 0.77 µg/mL, anti-BChE value was determined as 41.30 ± 0.48 µg/mL. It was also observed that the extract exhibited strong antiproliferative activities depending on the increase in concentration. As a result of LC-MS/MS analysis of the extract produced under optimum conditions in terms of phenolic content. The presence of fumaric, gallic, protocatechuic, 4-hydroxybenzoic, caffeic, 2-hydoxycinamic acids, quercetin and kaempferol was detected. As a result, it was determined that the H. spectabile extract produced under optimum conditions had significant effects in terms of biological activity.

利用人工神经网络结合遗传算法优化金丝桃提取物的生物活性。
优化萃取条件有助于最大限度地提高萃取过程的效率和产量,同时最大限度地减少对环境和人类健康的负面影响。本研究采用了人工神经网络(ANN)与遗传算法(GA)相结合的方法来优化金丝桃的提取条件。在这项特定的研究中,主要目标是使提取物的总抗氧化剂状态(TAS)达到尽可能高的水平。此外,还确定了表现出最大活性的提取物条件,并分析了在这些条件下获得的提取物的生物活性。提取温度为 30-60 °C,提取时间为 4-10 h,提取浓度为 0.25-2 mg/mL。从已建立的 ANN 模型中选出的最佳模型的平均绝对百分比误差(MAPE)值为 0.643%,平均平方误差(MSE)值为 0.004,相关系数(R)值为 0.996。遗传算法提出了最佳提取条件:提取温度为 59.391 ℃,提取时间为 8.841 h,提取浓度为 1.951 mg/mL。结论是 ANN-GA 的集成可成功用于优化金丝桃的提取参数。最佳条件下提取物的总抗氧化值为 9.306 ± 0.080 mmol/L,总氧化值为 13.065 ± 0.112 µmol/L,氧化应激指数为 0.140 ± 0.001。总酚含量(TPC)为 109.34 ± 1.29 mg/g,总黄酮含量(TFC)为 148.34 ± 1.48 mg/g。抗 AChE 值为 30.68 ± 0.77 µg/mL,抗 BChE 值为 41.30 ± 0.48 µg/mL。还观察到,随着浓度的增加,提取物表现出很强的抗增殖活性。LC-MS/MS 分析结果表明,在最佳条件下产生的提取物中酚类含量最高。检测到富马酸、没食子酸、原儿茶酸、4-羟基苯甲酸、咖啡酸、2-羟基琥珀酸、槲皮素和山柰酚的存在。结果表明,在最佳条件下提取的 H. spectabile 提取物具有显著的生物活性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
BMC Biotechnology
BMC Biotechnology 工程技术-生物工程与应用微生物
CiteScore
6.60
自引率
0.00%
发文量
34
审稿时长
2 months
期刊介绍: BMC Biotechnology is an open access, peer-reviewed journal that considers articles on the manipulation of biological macromolecules or organisms for use in experimental procedures, cellular and tissue engineering or in the pharmaceutical, agricultural biotechnology and allied industries.
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