The objective of this study was to determine the ultrasonication-assisted extraction conditions that maximize the DPPH radical scavenging activity of extracts obtained from the stems of Lespedeza bicolor Turcz through the application of the Response Surface Methodology (RSM). Before delving into the analysis of extraction conditions using the RSM model, we conducted efficiency validation of ultrasonication-assisted extraction and executed single-factor experiments for ethanol concentration, extraction time, and extraction temperature. The data obtained from these single-factor experiments were employed to construct the Box-Behnken Design (BBD). In these results, in the single-factor experiments, it was evident that the parameters for ethanol concentration, extraction time, and extraction temperature exhibited quadratic trends. The single-factor experiments allowed us to discern the trends for each parameter leading to the maximum antioxidant capacity, and this data was subsequently applied to the BBD. Following the completion of initial experiments, a Response Surface Methodology (RSM) model was constructed based on Box-Behnken Design (BBD). According to the predictive model developed in this study, it was anticipated that performing ultrasonic-assisted extraction for 85.0412 minutes at an ethanol concentration of 32.573% and an extraction temperature of 51.5608°C will result in a DPPH radical scavenging activity of 79.7146%. The predictive results were statistically verified through a comparative analysis with actual measurements and ANOVA analysis, confirming the statistical significance of the model. The finding of this study underscore the significance of optimizing extraction conditions in the precise quantification of the antioxidant potential for economic advantages in both experimental and industrial contexts.

Paecilomyces tenuipes (P. tenuipes) is a fungus cultivated artificially by South Korean researchers, utilizing rice bran as its substrate. The increased demand for this fungus has not been met with successful cultivation methods for fruiting body production in natural environments. Therefore, we tested the effect on the growth of P. tenuipes using a Solid media based on pests. In this results, the Solid media based on M.alternatus was effective in increasing the growth of P. tenuipes and the content of cordycepin. Moreover, we confirmed the conditions for manufacturing a Solid media based on M.alternatus for P. tenuipes growth. We suggested that the growth-promoting compounds offers valuable insights for optimizing fungal cultivation conditions, thereby enhancing productivity and contributing to a broader understanding of fungal physiology in varying nutritional environments.

Plants synthesize antioxidant compounds as a defense mechanism against reactive oxygen species. Recently, plant-derived antioxidant compounds have attracted attention due to the increasing consumer awareness in the heath industry. However, traditional methods for measuring the antioxidant activity of these compounds are time-consuming and costly. Therefore, our study constructed a quantitative structure-activity relationship (QSAR) model that can predict antioxidant activity using graph convolutional networks (GCN) from plant structural data. The accuracy (Acc) of the model reached 0.6 and the loss reached 0.03. Although with lower accuracy than previously reported QSAR models, our model showed the possibility of predicting DPPH antioxidant activity in a wide range of plant compounds (phenolics, polyphenols, vitamins, etc.) based on their graph structure.