Mushrooms are one of the indispensable elements of human diets. Edible mushrooms stand out with their aroma and nutritional properties. In this study, some biological activities of the wild edible mushroom Hericium erinaceus were determined. In this context, firstly, the most suitable extraction conditions of the fungus in terms of biological activity were determined. First, 64 different experiments were performed with the Soxhlet device under 40–70 °C extraction temperature, 3–9 h extraction time, and 0.5–2 mg/mL extraction conditions. As a result, a total antioxidant status (TAS) analysis was performed, and the extraction conditions were optimized so that the objective function was the maximum TAS value. The data obtained from the experimental study were modeled with artificial neural networks (ANNs), one of the artificial intelligence methods, and optimized with a genetic algorithm (GA). All subsequent tests were performed using the extract obtained under optimum extraction conditions. The antioxidant capacity of the mushroom was assessed using Rel assay kits and the DPPH and FRAP techniques. The agar dilution method was used to measure the antimicrobial activity. The anti-Alzheimer activity was assessed based on the activities of acetylcholinesterase (AChE) and butyrylcholinesterase (BChE). The antiproliferative activity was assessed against the A549 cancer cell line. The total phenolic content was measured using the Folin–Ciocalteu reagent. The measurement of total flavonoids was conducted using the aluminum chloride test. LC-MS/MS equipment was used to screen for the presence of standard chemicals. The optimum extraction conditions were found to be a 60.667 °C temperature, 7.833 h, and 1.98 mg/mL. It was determined that the mushroom has high antioxidant potential. It was determined that the substance was successful at combating common bacterial and fungal strains when used at dosages ranging from 25 to 200 µg/mL. The high antiproliferative effect of the substance was attributed to its heightened concentration. The anti-AChE value was found to be 13.85 μg/mL, while the anti-BChE value was confirmed to be 28.00 μg/mL. The phenolic analysis of the mushroom revealed the presence of 13 chemicals. This investigation found that H. erinaceus exhibits robust biological activity when extracted under appropriate circumstances.

In our study, the biological activities of the wild edible mushroom Cantharellus cibarius were determined. First of all, 64 different experiments were performed in the Soxhlet device at 40−70°C extraction temperatures, 4, 6, 8, and 10 h of extraction time and 0.25, 0.50, 1, and 2 mg/mL extract concentrations, and total antioxidant (TAS) and total oxidant values (TOS) were determined, and both single-purpose and multi-objective optimization studies were performed. The extraction conditions were optimized so that the objective function of the single-purpose optimization would be the maximum TAS value, and the objective function of the multi-objective optimization would be the maximum TAS and minimum TOS values. The data obtained from the experimental study were modeled with artificial neural networks from artificial intelligence methods, and optimization was performed with a genetic algorithm. After the single-objective optimization process, the optimum extraction conditions were found as 46.622°C, 5.110 h and 1.973 mg/mL and the multi-objective optimum extraction conditions were found as 50.927°C, 6.094 h and 1.439 mg/mL. The TAS values of the extracts obtained as a result of single-objective and multi-objective optimization were measured as 5.511 and 5.359, respectively, and the TOS values were measured as 7.289 and 6.061. The anti-AChE value of the extracts was calculated as 16.12, 20.31 and anti-BChE value as 36.92, 40.28. In addition, it was determined that the single-objective optimization extract had stronger antiproliferative activity than the multi-objective extract. As a result, it was determined that the biological activities of the extracts of C. cibarius obtained under suitable conditions were high.

The surface roughness of wood is affected by the processing conditions and the material structure. So, optimization of operation parameters is very crucial to have minimum surface roughness. In this study, modeling and optimization of surface roughness (R_a) of Scotch pine (Pinus sylvestris) was investigated. Firstly, the samples were cut under different conditions 8 mm, 9 mm and 11mm depth of cut and 12 mm, 14 mm and 16 mm axial depth of cut) in computer numerical control (CNC) machine, and then surface roughness (R_a) values of samples were calculated. Then a prediction model of surface roughness was developed using artificial neural networks (ANN). Optimization process was carried out to reach minimum surface roughness of wood samples by the genetic algorithm (GA) method. MAPE value of the ANN model was found lower than 4,0 %. The optimum CNC operation parameters were 1874,5 rad/s, 3,0 m/min feed rate, 9,7 mm depth of cut and 12 mm for axial depth of cut for minimum surface roughness. As a result of study, surface roughness of Scotch pine wood can be modeled and optimized using integrated ANN and GA methods by saving time and cost.

Many mushroom species have been used by people for different purposes, from past to present. Cultivated mushrooms may show different biological effects depending on the content of the substrate they grown on. The present study aimed to determine the total antioxidant status (TAS), total oxidant status (TOS) and oxidative stress index (OSI) of Pleurotus citrinopileatus Singer mushroom cultivated on five different substrates. The cultivated mushrooms were extracted with ethanol in a Soxhlet device. TAS, TOS and OSI of extracts were determined with Rel Assay kits. The highest TAS (3.125±0.038 mmol/L), TOS (10.786±0.313 µmol/L) and OSI (0.345±0.014) values were determined in the mushrooms grown on 90% beech sawdust+10% bran. The lowest TAS (2.316±0.042), TOS (1.246±0.044) and OSI (0.054±0.001) values were obtained from the mushrooms grown on 100% poplar sawdust.

In this study, extraction conditions were optimized to maximize the biological activities of extracts obtained from Paralepista flaccida, 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.