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优化[具体物质]的超声辅助提取工艺:基于响应面法和人工神经网络模型的抗氧化、抗胆碱酯酶及抗增殖活性比较研究

Optimizing Ultrasonic-Assisted Extraction Process of : A Comparative Study of Antioxidant, Anticholinesterase, and Antiproliferative Activities via Response Surface Methodology and Artificial Neural Network Modeling.

作者信息

Sevindik Mustafa, Gürgen Ayşenur, Korkmaz Aras Fahrettin, Akata Ilgaz

机构信息

Department of Biology, Faculty of Engineering and Natural Sciences, University of Osmaniye Korkut Ata, 80000 Osmaniye, Türkiye.

Department of Industrial Engineering, Faculty of Engineering and Natural Sciences, University of Osmaniye Korkut Ata, 80000 Osmaniye, Türkiye.

出版信息

Molecules. 2025 Aug 8;30(16):3317. doi: 10.3390/molecules30163317.

DOI:10.3390/molecules30163317
PMID:40871471
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC12388841/
Abstract

In this study, extraction conditions were optimized to maximize the biological activities of extracts obtained from , an edible mushroom species. Extraction processes were carried out using an ultrasonically assisted system, and two different optimization approaches were used as follows: Response Surface Methodology (RSM) and Artificial Neural Network-Genetic Algorithm (ANN-GA). The antioxidant potentials of the optimized extracts were evaluated using DPPH, FRAP, TAS, TOS, and OSI parameters; anticholinesterase activities were measured against AChE and BChE enzymes; and antiproliferative activities were investigated in A549, MCF-7, and DU-145 human cancer cell lines. In addition, phenolic contents were determined by LC-MS/MS analysis. The findings revealed that the extracts obtained by the RSM method exhibited a superior biological profile compared to ANN-GA extracts in terms of antioxidant, anticholinesterase, and antiproliferative activities. The high cytotoxicity observed, particularly in the MCF-7 line, supports the anticancer potential of this extract. These results demonstrate that optimization strategies are crucial for increasing not only extract yield but also biological functionality.

摘要

在本研究中,对提取条件进行了优化,以最大限度地提高从一种食用菌中获得的提取物的生物活性。提取过程采用超声辅助系统,并采用了以下两种不同的优化方法:响应面法(RSM)和人工神经网络-遗传算法(ANN-GA)。使用DPPH、FRAP、TAS、TOS和OSI参数评估优化提取物的抗氧化潜力;针对乙酰胆碱酯酶(AChE)和丁酰胆碱酯酶(BChE)测定抗胆碱酯酶活性;并在A549、MCF-7和DU-145人癌细胞系中研究抗增殖活性。此外,通过液相色谱-串联质谱(LC-MS/MS)分析测定酚类含量。研究结果表明,与ANN-GA提取物相比,通过RSM方法获得的提取物在抗氧化、抗胆碱酯酶和抗增殖活性方面表现出更优异的生物学特性。观察到的高细胞毒性,尤其是在MCF-7细胞系中,支持了该提取物的抗癌潜力。这些结果表明,优化策略不仅对于提高提取物产量至关重要,而且对于提高生物功能也至关重要。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/fe14/12388841/a6f20fb95955/molecules-30-03317-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/fe14/12388841/bdd428786a6c/molecules-30-03317-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/fe14/12388841/a8fc1a97e29e/molecules-30-03317-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/fe14/12388841/7e899b9f2682/molecules-30-03317-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/fe14/12388841/a6f20fb95955/molecules-30-03317-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/fe14/12388841/bdd428786a6c/molecules-30-03317-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/fe14/12388841/a8fc1a97e29e/molecules-30-03317-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/fe14/12388841/7e899b9f2682/molecules-30-03317-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/fe14/12388841/a6f20fb95955/molecules-30-03317-g004.jpg

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