OBJECTIVE:To establish a method for the simultaneous determination of scutellarin and linarin in Scoparia dulcis. METHODS:HPLC was performed on the column of Phenomenex C18 with mobile phase of acetonitrile-0.05% phosphoric acid (gradient elution)at a flow rate of 1.0 ml/min,the detection wavelength was 330 nm,column temperature was 30 ℃,and the in-jection volume was 10 μl. RESULTS:The linear range was 0.015 8-0.316 8 mg/ml for scutellarin(r=0.999 9)and 0.000 5-0.010 4 mg/ml for linarin (r=0.999 7);RSDs of precision,stability and reproducibility tests were lower than 3%;recoveries were 99.56%-102.38%(RSD=1.07%,n=6)and 95.14%-98.29%(RSD=1.24%,n=6),respectively. CONCLUSIONS:The method is simple with good stability and reprodicibility,and can be used for the simultaneous determination of scutellarin and linarin in S. du-lcis.

Objective:To explore the mechanism of Jianpi Qingchang Decoction in the treatment of UC by integrating network pharmacology, bioinformatics, molecular docking and experimental verification.Methods:The effective components and targets of Jianpi Qingchang Decoction were obtained from TCMSP database, and UC data sets GSE16879, GSE48958 and GSE75214 were obtained from GEO database, and differentially expressed genes were screened; intersection targets were obtained through Venn diagram, and GO function and KEGG pathway enrichment analysis was performed. An intersection target PPI network was constructed using STRING database and topology analysis was performed; hub genes were screened through lasso regression and the expression consistency of core targets in the dataset was verified through logistic regression. A UC mouse model was established and hub genes were validated.Results:A total of 213 drug targets of Jianpi Qingchang Decoction were obtained, and 499 common intersection targets of GSE16879, GSE48958 and GSE75214 were obtained by differential gene expression analysis. Thirty intersection targets of Jianpi Qingchang Decoction and UC were obtained, mainly acting on IL-17 signaling pathway, TNF signaling pathway, AGE-RAGE signaling pathway in diabetic complications, etc. PPI network topology analysis obtained 7 common intersection targets, including PTGS2, IL-1B, IL-6, MMP9, CXCL8, CCL2 and MMP2. IL-6 and MMP2 were selected as hub genes by lasso regression. Logistics regression analysis showed that IL-6 and MMP2 were risk factors for the disease. Compared with the model group, the expressions of IL-6 and MMP2 mRNA and protein in the colon tissue of the TCM group decreased ( P<0.05), and the morphology of colon tissue was improved compared with the model group. Conclusion:IL-6 and MMP2 are risk factors for UC, the therapeutic effect of Jianpi Qingchang Decoction is to mediate Il-17 signal pathway, TNF signal pathway and AGE-RAGE signal pathway in diabetic complications through the targets of IL-6, and MMP2, thereby treating UC.

Depression is a frequently-seen mental disorder that profoundly affects the survival and quality of life of individuals.Present clinical medicine therapies for depression are not fully efficacious and novel therapeutic agents and targets remain necessary.Bupleuri Radix-Paeoniae Radix(BR-PRA),an essential and crucial compo-nent of traditional antidepressant compound,possesses the beneficial effect of lowering toxicity and amplifying the antidepressant effect when utilized in combination.The underlying mechanisms of these synergistic effects may involve the suppression of inflammation and oxidative stress,the regulation of monoamine neurotransmitters,brain-derived neurotrophic factors,the modulation of the hypothalamus-pituitary-adrenal axis,and the metabolism of various amino acids and energy.This article summarizes the synergistic effects and antidepressant pharmacological effects of BR-PRA herb-pair,thereby providing valuable insights into the potential advantages of this combination and its potential mechanisms of antidepressant action.

Objective     To explore the correlation between the quantitative and qualitative features of CT images and the invasiveness of pulmonary ground-glass nodules, providing reference value for preoperative planning of patients with ground-glass nodules. Methods    The patients with ground-glass nodules who underwent surgical treatment and were diagnosed with pulmonary adenocarcinoma from September 2020 to July 2022 at the Third Affiliated Hospital of Kunming Medical University were collected. Based on the pathological diagnosis results, they were divided into two groups: a non-invasive adenocarcinoma group with in situ and minimally invasive adenocarcinoma, and an invasive adenocarcinoma group. Imaging features were collected, and a univariate logistic regression analysis was conducted on the clinical and imaging data of the patients. Variables with statistical difference were selected for multivariate logistic regression analysis to establish a predictive model of invasive adenocarcinoma based on independent risk factors. Finally, the sensitivity and specificity were calculated based on the Youden index. Results     A total of 555 patients were collected. The were 310 patients in the non-invasive adenocarcinoma group, including 235 females and 75 males, with a meadian age of 49 (43, 58) years, and 245 patients in the invasive adenocarcinoma group, including 163 females and 82 males, with a meadian age of 53 (46, 61) years. The binary logistic regression analysis showed that the maximum diameter (OR=4.707, 95%CI 2.060 to 10.758), consolidation/tumor ratio (CTR, OR=1.027, 95%CI 1.011 to 1.043), maximum CT value (OR=1.025, 95%CI 1.004 to 1.047), mean CT value (OR=1.035, 95%CI 1.008 to 1.063), spiculation sign (OR=2.055, 95%CI 1.148 to 3.679), and vascular convergence sign (OR=2.508, 95%CI 1.345 to 4.676) were independent risk factors for the occurrence of invasive adenocarcinoma (P<0.05). Based on the independent predictive factors, a predictive model of invasive adenocarcinoma was constructed. The formula for the model prediction was: Logit(P)=–1.293+1.549×maximum diameter of lesion+0.026×CTR+0.025×maximum CT value+0.034×mean CT value+0.72×spiculation sign+0.919×vascular convergence sign. The area under the receiver operating characteristic curve of the model was 0.910 (95%CI 0.885 to 0.934), indicating that the model had good discrimination ability. The calibration curve showed that the predictive model had good calibration, and the decision analysis curve showed that the model had good clinical utility. Conclusion     The predictive model combining quantitative and qualitative features of CT has a good predictive ability for the invasiveness of ground-glass nodules. Its predictive performance is higher than any single indicator.