Objective This study was aimed to investigate the effects of Ginger combined with Rhubarb on hyperuricemia in mice. Methods The mice hyperuricemic model was made by orally administering yeast extract, The mice were randomly divided into 7 groups,includinglow,middle and high dose of Ginger combined with Rhubarb group, Rhubarb group, and allopurinol group was given corresponding drugs respectively by gavage, and the uric acid (uA), creatinine (Cr), urea nitrogen (BUN) level in blood and XOD activity in liver were observed for all mice in each group. Results Compared to hyperuricaemia model control group,UA level and XOD activity in liver of mice of the three doses of Ginger combined with Rhubarb groups received dose-dependent decrease. Conclusion Ginger combined with Rhubarb can reduce UA level and XOD activity in liver in hyperuricaemia mice model.

Objective To study the optimal technology parameters of the enrichment process for total flavonoids of Crataegus pinnatifida Bge,with macroporous Resin. Methods The enrichment process was studied by orthogonal experiment design using orthogonal from L9(34) with the content of total flavonoids from Crataegus pinnatifida Bge,as indexes, the factors such as adsorption capacity, the column diameter-height ratio, eluant volume and adsorption time were investigated. Results The optimum elution parameters were as follows: the eluant volume of 60% alcohol—the wet resin amount (g)—the sample volume (mL) was 2:1, the sample was 4:1, the column diameter-height ratio was 1:6 , the adsorption time was 1h, respectively. Conclusion This process enriching the total flavonoids of Crataegus pinnatifida Bge,is feasible.

Objective:To evaluate the value of radiomics based on contrast-enhanced spectral mammography (CESM) of internal and peripheral regions combined with clinical factors in predicting benign and malignant breast lesions of breast imaging reporting and data system category 4 (BI-RADS 4).Methods:A retrospective analysis was performed on the clinical and imaging data of patients with breast lesions who were treated in Yantai Yuhuangding Hospital (Center 1) Affiliated to Qingdao University from July 2017 to July 2020 and in Fudan University Cancer Hospital (Center 2) from June 2019 to July 2020. Center 1 included 835 patients, all female, aged 17-80 (49±12) years, divided into training set (667 cases) and test set (168 cases) according to the "train-test-split" function in Python software at a ratio of 8∶2; and 49 patients were included from Center 2 as external validation set, all female, aged 34-70 (51±8) years. The radiomics features were extracted from the intralesional region (ITR), the perilesional regions of 5, 10 mm (PTR 5 mm, PTR10 mm) and the intra-and perilesional regions of 5, 10 mm (IPTR 5 mm, IPTR 10 mm) and were selected by variance filtering, SelectKBest algorithm, and least absolute shrinkage and selection operator. Then five radiomics signatures were constructed including ITR signature, PTR 5 mm signature, PTR 10 mm signature, IPTR 5 mm signature, IPTR 10 mm signature. In the training set, univariable and multivariable logistic regressions were used to construct nomograms by selecting radiomics signatures and clinical factors with significant difference between benign and malignant BI-RADS type 4 breast lesions. The efficacy of nomogram in predicting benign and malignant BI-RADS 4 breast lesions was evaluated by the receiver operating characteristic curve and area under the curve (AUC). Decision curve and calibration curve were used to evaluate the net benefit and calibration capability of the nomogram.Results:The nomogram included ITR signature, PTR 5 mm signature, PTR 10 mm signature, IPTR 5 mm signature, age, and BI-RADS category 4 subclassification for differentiating malignant and benign BI-RADS category 4 breast lesions and obtained AUCs of 0.94, 0.92, and 0.95 in the training set, test set, and external validation set, respectively. The calibration curve showed good agreement between the predicted probabilities and actual results and the decision curve indicated a good net benefit of the nomogram for predicting malignant BI-RADS 4 lesions in the training set, test set, and external validation set.Conclusion:The nomogram constructed from the radiomics features of the internal and surrounding regions of CESM breast lesions combined with clinical factors is attributed to differentiate benign from malignant BI-RADS category 4 breast lesions.