OBJECTIVE:To observe effects and safety of Kangfuxin solution combined with intense pulsed light in the treat-ment of rosacea. METHODS:A total of 50 rosacea patients in our hospital during May 2014-Jun. 2016 were divided into control group(25 cases)and observation group(25 cases)according to random number table. Based on oral administration of Metronida-zole tablets,control group received intense pulsed light. Observation group was additionally given Kangfuxin solution for local wet compress after 4 to 6 layers of gauze saturated with liquid,5-10 min,qn. Both groups received treatment for 4 weeks. Clinical effi-cacies,as well as symptom score and DLQI score were compared between 2 groups before and after treatment,and the occurrence of ADR was recorded. RESULTS:The response rate of observation group was 92.0%,which was significantly higher than 64.0%of control group,with statistical significance (P<0.05). Before treatment,there was no statistical significance in erythema,pap-ules,pustules,itching,telangiectasia score and total score,DLQI score with before treatment(P>0.05). After treatment,erythe-ma,papules,pustules,itching,telangiectasia score and total score,DLQI score of 2 groups were decreased significantly,and the observation group was significantly lower than the control group,with statistical significance(P<0.05). The incidence of ADR in observation group was 16.0%,which was significantly lower than 40.0% in control group,with statistical significance(P<0.05). CONCLUSIONS:Kangfuxin solution combined with intense pulsed light show significant efficacy for rosacea,and can effectively improve erythema,papules,pustules,itching and telangiectasia,and improve the quality of life with good safety.

Abstract Biomarkers could improve the understanding of the causes of obesity and its association with chronic diseases for people. The purpose of the review is to summarize recent advances in transcriptomic, proteomic, and metabolomic phenotypic biomarkers of obesity in order to deepen the understanding of the etiology of obesity and its metabolic consequences. In the precise prevention and control of childhood obesity, different groups of biomarkers can improve the accuracy of the word "obesity" and help early detection of specific biomarkers with risk characteristics, so as to realize the transformation of childhood obesity from a one size fits all prevention and control strategy to a personalized prevention and control plan during the development of obesity.

Objective: To investigate the effect of Baohuoside-Ⅰ on the proliferation, invasion, migration and apoptosis of colon cancer cell lines SW480 and RKO and the relative mechanism. Methods: Colon cancer cell lines SW480 and RKO were respectively treated with different concentrations of Baohuoside-Ⅰ (0, 5, 10, 20 μg/ml). Cell proliferation was detected by MTT assay; The ability of cell clone formation was tested by cell clone formation experiments; The migration and invasion of cells were detected by Transwell assay; The apoptosis and cell cycle was detected by Flow cytometry; and the protein expression levels of cleaved PARP, cleaved Caspase-3 and Bcl-2 were detected by Western blotting. TheeffectsofBaohuoside-Ⅰontranscriptomeandpossiblesignaling pathways were detected by RNA-Seq technology. Results: Baohuoside-Ⅰ could inhibit the proliferation, invasion and migration of SW480 and RKO cells, and induce cell apoptosis and G0/G1 phase block. Baohuoside-Ⅰ could also up-regulate the protein expressions of cleaved PARP and cleaved Caspase-3 but down-regulate the protein expression of Bcl-2 in SW480 and RKO cell lines. In addition, RNA-Seq data analysis showed that DNAreplication and transcription of ERBB signaling pathway related genes were both affected by Baohuoside-Ⅰ. Conclusion: Baohuoside-Ⅰ could induce apoptosis and G0/G1 phase block of colon cancer cell lines SW480 and RKO by affecting the expression of apoptosis related proteins, as well as cellular DNA replication and ERBB signaling pathways, thus inhibiting the malignant phenotypes of SW480 and RKO.

ObjectiveThis study aims to develop a prediction model for the compatibility of Chinese medicinal pairs based on Graph Convolutional Networks （GCN）， named HC-GCN. The model integrates the properties of herbs with modern pharmacological mechanisms to predict pairs with specific therapeutic effects. It serves as a demonstration by applying the model to predict and validate the efficacy of blood-activating herb pairs. MethodsThe training dataset for herb pair prediction was constructed by systematically collecting commonly used herb pairs along with their characteristic data， including Qi， flavor， meridian tropism， and target genes. Integrating traditional characteristics of herb with modern bioinformatics， we developed an efficacy-oriented herb pair compatibility prediction model （HC-GCN） using graph convolutional networks （GCN）. This model leverages machine learning to capture the complex relationships in herb pair compatibility， weighted by efficacy features. The performance of the HC-GCN model was evaluated using accuracy （ACC）， recall， precision， F1 score （F1）， and area under the ROC curve （AUC）. Its predictive effectiveness was then compared to five other machine learning models： eXtreme Gradient Boosting （XGBoost）， logistic regression （LR）， Naive Bayes， K-nearest neighbor （KNN）， and support vector machine （SVM）. ResultsUsing herb pairs with blood-activating effects as a demonstration， a prediction model was constructed based on a foundational dataset of 46 blood-activating herb pairs， incorporating their Qi， flavor， meridian tropism， and target gene characteristics. The HC-GCN model outperforms other commonly used machine learning models in key performance metrics， including ACC， recall， precision， F1 score， and AUC. Through the predictive analysis of the HC-GCN model， 60 herb pairs with blood-activating effects were successfully identified. Among of these potential herb pairs， 44 include at least one herb with blood-activating effects. ConclusionIn this study， we established an efficacy-oriented compatibility prediction model for herb pairs based on GCN by integrating the unique characteristics of traditional herbs with modern pharmacological mechanisms. This model demonstrated high predictive performance， offering a novel approach for the intelligent screening and optimization of traditional Chinese medicine prescriptions， as well as their clinical applications.