ObjectiveTo explore the potential mechanism of action of the combination of Sanguisorbae Radix-Sophorae Flos （DH） in the treatment of ulcerative colitis （UC） using network pharmacology methods and molecular docking technology. MethodsNetwork pharmacology analysis was utilized to predict the potential targets of DH for the treatment of UC. The therapeutic effects were experimentally validated by inducing a UC model in mice with 3% dextran sulfate sodium （DSS）. The experimental groups were the normal group， the model group， the salazosulfapyridine group （100 mg·kg^-1）， and the low， medium， and high dose groups of DH （1.2， 2.4， and 4.8 g·kg^-1）. The efficacy of the treatment was assessed through the general condition of the mice， histopathological examination， and the expression levels of inflammatory markers in the colon. The effect of DH on angiogenesis was explored by messenger RNA （mRNA） detection of colonic angiogenesis-related mediators， vascular endothelial growth factor （VEGF） immunohistochemistry， microvessel density （MVD） detection， and transmission electron microscopy. The phosphatidylinositol-3-kinase （PI3K）-protein kinase B （Akt） signaling pathway proteins were quantitatively analyzed through Western blot to assess whether the suppression of pathological angiogenesis by DH is associated with this pathway. ResultsNetwork pharmacological analysis yielded 112 potential core therapeutic targets for the treatment of UC with DH， of which the core targets were tumor protein 53 （TP53）， JUN， interleukin （IL）-6， Akt1， and tumor necrosis factor （TNF）. Compared with the normal group， mice in the model group showed significant weight loss， colon shortening， and high DAI score， increased expression of inflammatory factors IL-6， IL-1β， and TNF-α， as well as increased mRNA expression levels of angiogenesis-related mediators VEGF， vascular cell adhesion molecule 1 （VCAM1）， angiotensin 1 （Ang1）， matrix metalloproteinase （MMP）-1， MMP-2， and MMP-9. The positive expression of CD31 and VEGF in colonic tissue increased， and the protein expression of the PI3K/Akt pathway was increased （P<0.05）. The endothelial cells of the colonic mucosa and the colonic vasculature were severely damaged. Compared with the model group， mice in the DH groups had significantly reduced weight loss and colon shortening， lower DAI scores， and a significant decrease in mRNA expression of inflammatory factors and angiogenesis-related mediators. In addition， there was decreased positive expression of CD31 and VEGF in colonic tissue and decreased protein expression of the PI3K/Akt pathway （P<0.05）. ConclusionNetwork pharmacology， molecular docking， and experimental validation are applied to explore the mechanism of action of DH in the treatment of UC， and it is found that DH is able to improve the symptoms of colitis and inhibit the pathological angiogenesis in UC mice. Its action might be related to affecting the PI3K/Akt pathway.

ObjectiveTo explore the potential mechanism of action of the combination of Sanguisorbae Radix-Sophorae Flos （DH） in the treatment of ulcerative colitis （UC） using network pharmacology methods and molecular docking technology. MethodsNetwork pharmacology analysis was utilized to predict the potential targets of DH for the treatment of UC. The therapeutic effects were experimentally validated by inducing a UC model in mice with 3% dextran sulfate sodium （DSS）. The experimental groups were the normal group， the model group， the salazosulfapyridine group （100 mg·kg^-1）， and the low， medium， and high dose groups of DH （1.2， 2.4， and 4.8 g·kg^-1）. The efficacy of the treatment was assessed through the general condition of the mice， histopathological examination， and the expression levels of inflammatory markers in the colon. The effect of DH on angiogenesis was explored by messenger RNA （mRNA） detection of colonic angiogenesis-related mediators， vascular endothelial growth factor （VEGF） immunohistochemistry， microvessel density （MVD） detection， and transmission electron microscopy. The phosphatidylinositol-3-kinase （PI3K）-protein kinase B （Akt） signaling pathway proteins were quantitatively analyzed through Western blot to assess whether the suppression of pathological angiogenesis by DH is associated with this pathway. ResultsNetwork pharmacological analysis yielded 112 potential core therapeutic targets for the treatment of UC with DH， of which the core targets were tumor protein 53 （TP53）， JUN， interleukin （IL）-6， Akt1， and tumor necrosis factor （TNF）. Compared with the normal group， mice in the model group showed significant weight loss， colon shortening， and high DAI score， increased expression of inflammatory factors IL-6， IL-1β， and TNF-α， as well as increased mRNA expression levels of angiogenesis-related mediators VEGF， vascular cell adhesion molecule 1 （VCAM1）， angiotensin 1 （Ang1）， matrix metalloproteinase （MMP）-1， MMP-2， and MMP-9. The positive expression of CD31 and VEGF in colonic tissue increased， and the protein expression of the PI3K/Akt pathway was increased （P<0.05）. The endothelial cells of the colonic mucosa and the colonic vasculature were severely damaged. Compared with the model group， mice in the DH groups had significantly reduced weight loss and colon shortening， lower DAI scores， and a significant decrease in mRNA expression of inflammatory factors and angiogenesis-related mediators. In addition， there was decreased positive expression of CD31 and VEGF in colonic tissue and decreased protein expression of the PI3K/Akt pathway （P<0.05）. ConclusionNetwork pharmacology， molecular docking， and experimental validation are applied to explore the mechanism of action of DH in the treatment of UC， and it is found that DH is able to improve the symptoms of colitis and inhibit the pathological angiogenesis in UC mice. Its action might be related to affecting the PI3K/Akt pathway.

Perceptual decision making refers to the process by which individuals make choices and judgments based on sensory information, serving as a fundamental ability for human adaptation to complex environments. While traditional research has focused on perceptual decision making in isolated contexts, growing evidence highlights the profound influence of social contexts prevalent in real-world scenarios. As a crucial factor supporting individual survival and development, social context not only provides rich information sources but also shapes perceptual decision making through top-down processing mechanisms, prompting researchers to recognize the inherently social nature of human decisions. Empirical studies have demonstrated that social information, such as others’ choices or group norms, can systematically bias individuals’ perceptual decisions, often manifesting as conformity behaviors. Social influence can also facilitate performance under certain conditions, particularly when individuals can accurately identify and adopt high-quality social information. The impact of social context on perceptual decisions is modulated by a variety of external and internal factors, including group characteristics(e.g., group size, response consistency), attributes of peers (e.g., familiarity, social status, distinctions between human and artificial agents), as well as individual differences such as confidence, personality traits, and developmental stage. The motivations driving social influence encompass three primary mechanisms: improving decision accuracy through informational influence, gaining social acceptance through normative influence, and maintaining positive self-concept. Recent computational approaches have employed diverse theoretical frameworks to provide valuable insights into the cognitive mechanisms underlying social influence in perceptual decision making. Reinforcement learning models demonstrate how social feedback shapes future choices through reward-based updating. Bayesian inference frameworks describe how individuals integrate personal beliefs with social information based on their respective reliabilities, dynamically updating beliefs to optimize decisions under uncertainty. Drift diffusion models offer powerful tools to decompose social influence into distinct cognitive components, allowing researchers to differentiate between changes in perceptual processing and shifts in decision criteria. Collectively, these models establish a comprehensive methodological foundation for disentangling the multiple pathways by which social context shapes perceptual decisions. Neuroimaging and electrophysiological studies provide converging evidence that social context influences perceptual decision making through multi-level neural mechanisms. At early perceptual processing stages, social influence modulates sensory evidence accumulation in parietal cortex and directly alters primary visual cortex activity, while guiding selective attention to stimulus features consistent with social norms through attentional alignment mechanisms. At higher cognitive levels, the reward system (ventral striatum, ventromedial prefrontal cortex) is activated during group-consistent decisions; emotion-processing networks (anterior cingulate cortex, insula, amygdala) regulate experiences of social acceptance and rejection; and mentalizing-related brain regions (dorsomedial prefrontal cortex, temporoparietal junction) support inference of others’ mental states and social information integration. These neural circuits work synergistically to achieve top-down multi-level modulation of perceptual decision making. Understanding the mechanisms by which social context shapes perceptual decision making has broad theoretical and practical implications. These insights inform the optimization of collective decision-making, the design of socially adaptive human-computer interaction systems, and interventions for cognitive disorders such as autism spectrum disorder and anorexia nervosa. Future studies should combine computational modeling and neuroimaging approaches to systematically investigate the multi-level and dynamic nature of social influences on perceptual decision making.

Objective Data mining technology was used to mine the medication rules of the prescriptions used in the treatment of pediatric atopic dermatitis by Chinese medical master XUAN Guo-Wei.Methods The medical records of effective cases of pediatric atopic dermatitis treated by Professor XUAN Guo-Wei at outpatient clinic were collected,and then the medical data were statistically analyzed using frequency statistics,association rule analysis and cluster analysis.Results A total of 242 prescriptions were included,involving 101 Chinese medicinals.There were 23 commonly-used herbs,and the 16 high-frequency herbs(frequency＞100 times)were Glycyrrhizae Radix et Rhizoma,Saposhnikoviae Radix,Glehniae Radix,Perillae Folium,Ophiopogonis Radix,Cynanchi Paniculati Radix et Rhizoma,Microctis Folium,Dictamni Cortex,Scrophulariae Radix,Coicis Semen,Cicadae Periostracum,Lilii Bulbus,Rehmanniae Radix,Kochiae Fructus,Sclerotium Poriae Pararadicis,and Euryales Semen.The analysis of the medicinal properties showed that most of the herbs were sweet and cold,and mainly had the meridian tropism of the spleen,stomach and liver meridians.The association rule analysis yielded 24 commonly-used drug combinations and 20 association rules.Cluster analysis yielded 2 core drug combinations.Conclusion For the treatment of pediatric atopic dermatitis,Professor XUAN Guo-Wei focuses on the clearing,supplementing and harmonizing therapies,and the medication principle of"supporting the healthy-qi to eliminate the pathogen,and balancing the yin and yang"is applied throughout the treatment.

Epilepsy is a common neurological disease,has the characteristics of recurrent attacks and long-term treatment,thus bringing great pressure to patients and their families.Therefore,it is particularly important to do a good job of disability assessment.In recent years,with the development of the discipline,academic organizations such as the International League Against Epilepsy(ILAE)and China Association Against Epilepsy(CAAE)have successively updated the definition and diagnostic criteria of epilepsy and seizures.However,some items of epilepsy in the current Criteria for Disability Rating of Military Personnel(Trial)issued by People's Liberation Army(PLA)in 2011 can no longer meet the latest guidelines at home and abroad.Therefore,we suggest that the items related to epilepsy in the Criteria for Disability Rating of Military Personnel(Trial)should be revised to ensure that the disability evaluation being completed fairly and successfully.

Objective An isotemporal substitution model was used to explore the associations between activities including 10 minutes per day of physical activity(PA),sedentary behavior(SB),and sleep(SLP),and depressive symptoms among vocational school students with and without depressive symptoms.Methods Questionnaire survey was conducted on grade one to grade three students attending vocational schools in Shanghai and Jiangsu Province from Dec 2021 to Jan 2022.Fourteen schools were selected using the convenience cluster sampling method.The selected students were categorized into depressive symptoms group and non-depressive symptoms group according to the Centre for Epidemiologic Studies Depression Scale(CES-D)scores.Results A total of 40 339 questionnaires were collected,of which 10 086 were able to clearly remember the time of physical activity in the past week,and 8 149 were valid after data cleaning.According to the valid questionnaires,5 496 students(67.44%)were in the non-depressive symptoms group and 2 653(32.56%)were in the depressive symptoms group.The mean age of the students were(16.70±1.19)years.In the non-depressive symptoms group,substituting moderate physical activity(MPA)for all the other behaviors was negatively associated with CES-D scores,while substituting vigorous physical activity(VPA)for MPA and SB was positively associated with CES-D scores.In the depressive symptoms group,substituting walking,SB,and SLP with MPA was negatively associated with CES-D scores,respectively.The associations of MPA substituted for walking,SB,and SLP with CES-D scores were much stronger in the depressive symptoms group than in the non-depressive symptoms group.Conclusion The detection rate of depressive symptoms was high among vocational students.Substituting MPA for walking,SB,and SLP were negatively associated with CES-D scores,with a stronger association observed in the depressive symptoms group than in the non-depressive symptoms group.

Objective To investigate the implementation of surveillance,prevention and control measures for healthcare-associated infection(HAI)in maternal and child healthcare(MCH)institutions,and provide policy evi-dence for optimizing HAI prevention and control in MCH institutions.Methods Stratified sampling was conducted among the MCH institutions at provincial,municipal and county levels in 8 provinces/autonomous regions.A uni-fied questionnaire was designed and the online survey was conducted through"Questionnaire Star".Results The data from 123 MCH institutions were included in the analysis.90.24％of the MCH institutions carried out compre-hensive surveillance on HAI.The ratios of MCH institutions which implemented targeted surveillance on HAI in neonatal intensive care unit(NICU),surgical site infection,multidrug-resistant organisms(MDROs)and HAI in intensive care units(non-NICU excluded)were 89.66％,85.96％,80.77％,and 74.19％,respectively.51.22％MCH institutions adopted information surveillance system on HAI cases.94.31％MCH institutions carried out surveillance on hand hygiene compliance.Over 90％MCH institutions carried out surveillance on environment hy-giene in high-risk departments.71.54％MCH institutions conducted centralized cleaning,disinfection,sterilization and supply for reusable medical instruments in the central sterile supply department(CSSD).Over 90％MCH insti-tutions established three-level pre-examination triage systems.86.18％set up transitional wards.MCH institutions generally adopted a management model with established effective communication,full appointment visits,and sepa-rate visits for special medical groups,such as registered pregnant women,high-risk newborns,healthcare groups,and long-term rehabilitation patients.However,the ratio of institutions conducting on-line follow-up visits was less than 50％.Conclusion MCH institutions have generally carried out comprehensive and targeted surveillance on HAI.Information surveillance need to be facilitated.Hand hygiene and environmental hygiene surveillance has been popularized to a certain extent at all levels of MCH institutions.The cleaning,disinfection,sterilization,and supply processes of reusable medical devices in a few MCH institutions are not standardized.Special medical populations get effective management.On-line healthcare is to be further promoted.

AIM To establish a UPLC-MS/MS method for the simultaneous content determination of liquiritin apioside,alibiflorin,swertiamarin,methyl gallate,benzoylpaeoniflorin,sweroside,6′-O-β-D-glucosylgentiopicroside,isoliquiritigenin,loganic acid,liquiritigenin,gallic acid,paeoniflorin,oxypaeoniflorin,gentiopicroside,glycyrrhizic acid,isoliquiritoside and liquiritin in Yangxue Ruanjian Capsules.METHODS The analysis was performed on a 40℃thermostatic Waters BEH C18column(2.1 mm×100 mm,1.7 μm),with the mobile phase comprising of 2 mmol/L ammonium acetate(containing 0.1%formic acid)-acetonitrile flowing at 0.3 mL/min in a gradient elution manner,and electron spray ionization source was adopted in negative ion scanning with multiple reaction monitoring mode.RESULTS Seventeen constituents showed good linear relationships within their own ranges(r>0.999 6),whose average recoveries were 91.33%-104.03%with the RSDs of 1.58%-3.50%.CONCLUSION This rapid,accurate and stable method can be used for the quality control of Yangxue Ruanjian Capsules.

AIM To investigate the variation rules of main secondary metabolites in Hedysari Radix before and after rubbing strip.METHODS UPLC-MS/MS was adopted in the content determination of formononetin,ononin,calycosin,calycosin-7-glucoside,medicarpin,genistein,luteolin,liquiritigenin,isoliquiritigenin,vanillic acid,ferulic acid,γ-aminobutyric acid,adenosine and betaine,after which cluster analysis,principal component analysis and orthogonal partial least squares discriminant analysis were used for chemical pattern recognition to explore differential components.RESULTS After rubbing strip,formononetin,calycosin,liquiritigenin and γ-aminobutynic acid demonstrated increased contents,along with decreased contents of ononin,calycosin-7-glucoside and vanillic acid.The samples with and without rubbing strip were clustered into two types,calycosin-7-glucoside,formononetin,γ-aminobutynic acid,vanillic acid,calycosin-7-glucoside and formononetin were differential components.CONCLUSION This experiment clarifies the differences of chemical constituents in Hedysari Radix before and after rubbing strip,which can provide a reference for the research on rubbing strip mechanism of other medicinal materials.

Objective To construct a machine learning prediction model for postoperative liver injury in patients with non-liver surgery based on preoperative and intraoperative medication indicators.Methods A case-control study was conducted on 315 patients with liver injury after non-liver surgery selected from the databases developed by 3 large general hospitals from January 2014 to September 2022.With the positive/negative ratio of 1 ∶3,928 cases in corresponding period with non-liver surgery and without liver injury were randomly matched as negative control cases.These 1243 patients were randomly divided into the modeling group(n=869)and the validation group(n=374)in a ratio of 7∶3 using the R language setting code.Preoperative clinical indicators(basic information,medical history,relevant scale score,surgical information and results of laboratory tests)and intraoperative medication were used to construct the prediction model for liver injury after non-liver surgery based on 4 machine learning algorithms,k-nearest neighbor(KNN),support vector machine linear(SVM),logic regression(LR)and extreme gradient boosting(XGBoost).In the validation group,receiver operating characteristic(ROC)curve,precision-recall curve(P-R),decision curve analysis(DCA)curve,Kappa value,sensitivity,specificity,Brier score,and F1 score were applied to evaluate the efficacy of model.Results The model established by 4 machine learning algorithms to predict postoperative liver injury after non-liver surgery was optimal using the XGBoost algorithm.The area under the receiver operating characteristic curve(AUROC)was 0.916(95%CI:0.883～0.949),area under the precision-recall curve(AUPRC)was 0.841,Brier score was 0.097,and sensitivity and specificity was 78.95%and 87.10%,respectively.Conclusion The postoperative liver injury prediction model for non-liver surgery based on the XGBoost algorithm has effective prediction for the occurrence of postoperative liver injury.