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Gastric cancer (GC) is the third leading cause of cancer death worldwide. In the field of medicine, machine learning is widely used in genetic data mining and the construction of diagnostic models. This study proposed an intelligent model DERFS-XGBoost for rapid and accurate diagnosis of GC based on gene expression data. Firstly, the data of GC were collected and preprocessed. Secondly, ANOVA, t-test and fold chang (FC) were used to select genes that had significant differentially expressed genes (DEGs), and random forest (RF) was used to calculate their importance, and then sequential forward selection (SFS) was used to obtain the optimal feature subset. Finally, XGBoost was used for classification after synthetic minority oversampling technique (SMOTE) balanced between tumor and normal samples. In order to objectively evaluate the results, the 10-fold cross-validation and 10 repeated experiments were used in the experiment, and the average value of the evaluation indexes was used to evaluate the classification effect. Based on the experiment, DERFS-XGBoost model accuracy rate was 97.6%, precision was 100%, the recall rate was 97.3%, F1 was 99%, and the area under the ROC receiver operating characteristic curve AUC was 98.7%. The DERFS-XGBoost model has new characteristics which are different from existing diagnostic models, and has achieved a high classification effect with a small number of genes in comparison tests, which provides a new method and basis for the diagnosis of GC. [ABSTRACT FROM AUTHOR]

Pectinex XXL, a commercially prepared pectinase, was investigated for its potential application in the fruit juice industry. Polygalacturonic acid was used as the substrate for determining the enzymatic properties of Pectinex XXL using the DNS method. According to the results, the optimal pH for Pectinex XXL activity was 4.5, and the enzyme was stable in the pH range of 3.0~4.5. The optimal pH and pH stability range are consistent with those of some tropical and subtropical fruits. The optimal temperature for Pectinex XXL activity was 60 °C, and the enzyme remained stable after one hour in a water bath set at 40 C . Additionally, the enzymatic activity was not inhibited in the presence of 1 mmol/L of Na+, Mg2+, Ba2+, Co2+, Zn2+, and Fe2+, whereas it was slightly inhibited in the presence of 2 mmol/L of K+ and Fe2+ and partially inhibited in the presence of 1 and 2 mmol/L of Ca2+ and Mn2+, demonstrating its good stability in acids and excellent thermal catalytic performance. Based on the above experimental results, depectinization experiments were performed on plantain and cherry tomato juices using different amounts of Pectinex XXL. After one hour reaction with 16 U/mL of the enzyme, the yields of the plantain and cherry tomato juices were substantially increased by 119.03% and 15.97%, respectively, while their light transmittance was remarkably enhanced by 37.65% and 12.35%, respectively. Furthermore, the enzyme reduced the viscosity of the plantain and cherry tomato juices by 88.29% and 29.50%, respectively. The juice production experiments confirmed that this enzyme can significantly improve the yield and light transmittance of plantain juice, while effectively reducing its viscosity. These findings indicate the potential of Pectinex XXL in the industrial production of plantain juice. [ABSTRACT FROM AUTHOR]

Competitive implications of cross-holdings have been extensively analyzed in the literature. Incentives for engaging cross-holdings and welfare effects were however rarely studied. Although a similar logic as with the merger paradox holds for Cournot oligopolies with homogeneous products and symmetric technologies, we show that there are profit incentives for firms to engage cross-holdings with asymmetric technologies. Furthermore, we show that social welfare could be enhanced with cross-holdings even though the market becomes more concentrated. We also discuss the robustness of both the submodularity of the Cournot model with respect to the presence of cross-holdings and our results with respect to product differentiation. [ABSTRACT FROM AUTHOR]