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Chinese medicine extracts are currently the hotspot of new drug research and development. Herein, we report the mechanism of action of the traditional Chinese medicine extract Forsythiaside A in the treatment of male infertility and experimental verification. We first obtained 95 intersection genes between the target protein of Forsythiaside A and the target genes of male infertility and screened 13 key genes. In molecular docking, Forsythiaside A can each have a higher total docking score with 12 key genes and have a better combination. These 95 intersection genes are mainly related to biological processes such as response to peptide hormone, response to oxidative stress, and participation in the oxidative stress of the forkhead box O (FoxO) signaling pathway. Therefore, we use ornidazole to induce an experimental model of oligoasthenospermia in rats and use different concentrations of Forsythiaside A to intervene. We proved that the semen quality and superoxide dismutase (SOD) activities of model group rats were significantly lower than those of the blank group, and semen quality and SOD activities of the low-dose group and high-dose group were significantly higher than those of the model group. The malondialdehyde (MDA) level of model group rats was significantly higher than that of blank group, while the MDA levels of the low-dose group and high-dose group were significantly lower than that of the model group. Forsythoside A is a potential drug substance for male infertility and improves the semen quality, MDA levels, and SOD activities of rats with oligoasthenospermia.

Objective To evaluate the value of ultrasound-based radiomics in the preoperative prediction of type I and type II epithelial ovarian cancer. Methods A total of 154 patients with epithelial ovarian cancer were enrolled retrospectively. There were 102 unilateral lesions and 52 bilateral lesions among a total of 206 lesions. The data for the 206 lesions were randomly divided into a training set (53 type I + 71 type II) and a test set (36 type I + 46 type II) by random sampling. ITK-SNAP software was used to manually outline the boundary of the tumor, that is, the region of interest, and 4976 features were extracted. The quantitative expression values of the radiomics features were normalized by the Z-score method, and the 7 features with the most differences were screened by using the Lasso regression tenfold cross-validation method. The radiomics model was established by logistic regression. The training set was used to construct the model, and the test set was used to evaluate the predictive efficiency of the model. On the basis of multifactor logistic regression analysis, combined with the radiomics score of each patient, a comprehensive prediction model was established, the nomogram was drawn, and the prediction effect was evaluated by analyzing the area under the receiver operating characteristic curve (AUC), calibration curve and decision curve. Results The AUCs of the training set and test set in the radiomics model and comprehensive model were 0.817 and 0.731 and 0.982 and 0.886, respectively. The calibration curve showed that the two models were in good agreement. The clinical decision curve showed that both methods had good clinical practicability. Conclusion The radiomics model based on ultrasound images has a good predictive effect for the preoperative differential diagnosis of type I and type II epithelial ovarian cancer. The comprehensive model has higher prediction efficiency.