Optimizing Ultrasonic-Assisted Extraction Process of Paralepista flaccida: A Comparative Study of Antioxidant, Anticholinesterase, and Antiproliferative Activities via Response Surface Methodology and Artificial Neural Network Modeling
Мustafa Sevindik, Ayşenur Gürgen, Ahmet Korkmaz, İlgaz Akata
Abstract
, 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.