OBJECTIVE To evaluate the efficacy， safety and cost-effectiveness of deucravacitinib in the treatment of moderate- to-severe plaque psoriasis. METHODS Rapid health technology assessment （HTA） reports， systematic reviews （SR）/meta- analyses， and pharmacoeconomic studies on deucravacitinib for the treatment of moderate-to-severe plaque psoriasis were identified by searching PubMed， Web of Science， Embase， CNKI， Wanfang data and official HTA websites. The search time frame spanned from database inception to July 2025. After literature screening， data extraction， and quality assessment， the study results were subjected to descriptive analysis and synthesis. RESULTS A total of 14 articles were finally included， consisting of 1 HTA report， 10 SR/meta-analyses， and 3 pharmacoeconomic studies. Regarding efficacy， deucravacitinib demonstrated superior efficacy to both placebo and apremilast， with significantly higher response rates for Psoriasis Area and Severity Index 50/75/90/100， Static Physician’ s Global Assessment 0/1， and Dermatology Life Quality Index 0/1， as well as greater reduction in Psoriasis Symptoms and Signs Diary Score （P＜0.05）. Regarding safety， deucravacitinib was well-tolerated. Although the overall incidence of adverse events （AEs） was higher than placebo， it was not significantly different from apremilast. Moreover， the incidence of serious AEs and the rate of discontinuation due to AEs did not differ significantly from placebo （P＞0.05）. Regarding cost-effectiveness， deucravacitinib proved to be more cost-effective than apremilast across multiple healthcare system perspectives， including those of the United States， Japan， and China. CONCLUSIONS Deucravacitinib exhibits favorable efficacy， safety， and cost-effectiveness in the treatment of moderate-to-severe plaque psoriasis. Additional real-world studies are warranted to further refine its evaluation.

To explore the advantages of traditional Chinese medicine （TCM） and integrative TCM-Western medicine approaches in the treatment of diabetic microvascular complications （DMC）， refine key pathophysiological insights and treatment principles， and promote academic innovation and strategic research planning in the prevention and treatment of DMC. The 38th session of the Expert Salon on Diseases Responding Specifically to Traditional Chinese Medicine， hosted by the China Association of Chinese Medicine， was held in Beijing， 2024. Experts in TCM， Western medicine， and interdisciplinary fields convened to conduct a systematic discussion on the pathogenesis， diagnostic and treatment challenges， and mechanism research related to DMC， ultimately forming a consensus on key directions. Four major research recommendations were proposed. The first is addressing clinical bottlenecks in the prevention and control of DMC by optimizing TCM-based evidence evaluation systems. The second is refining TCM core pathogenesis across DMC stages and establishing corresponding "disease-pattern-time" framework. The third is innovating mechanism research strategies to facilitate a shift from holistic regulation to targeted intervention in TCM. The fourth is advancing interdisciplinary collaboration to enhance the role of TCM in new drug development， research prioritization， and guideline formulation. TCM and integrative approaches offer distinct advantages in managing DMC. With a focus on the diseases responding specifically to TCM， strengthening evidence-based support and mechanism interpretation and promoting the integration of clinical care and research innovation will provide strong momentum for the modernization of TCM and the advancement of national health strategies.

ObjectiveTo systematically evaluate the application of narrative education in undergraduate nursing teaching， to understand the current application status of narrative education， and to provide a theoretical basis for the subsequent establishment of a sound narrative education system. MethodsA systematic search was conducted for studies published in Chinese and English databases on applying narrative education to undergraduate nursing teaching， with the search period ranging from database inception to February 23， 2025. Literature was screened， and relevant information was extracted. A rigorous quality evaluation was conducted on the included studies， and a descriptive analysis was performed on their content. ResultsA total of 20 papers were included， involving 3，180 research subjects， all of whom were undergraduate nursing students. The results of descriptive analysis showed that the teaching model of narrative education primarily encompassed reading narrative works， watching films and videos， performing narrative scenarios， and writing reflective journals. The course setting and content covered pre-teaching preparation and in-teaching implementation. The evaluation of teaching effectiveness included the evaluation of teachers’ teaching methods （student evaluation/self-evaluation） and the evaluation of students’ learning effectiveness （course grade evaluation/humanistic care scale/empathy scale assessment， and others）. ConclusionNarrative education combines abstract concepts with concrete clinical situations， which not only enriches students’ learning experiences but also enhances their humanistic literacy. Meanwhile， it provides teachers with opportunities to develop their narrative teaching skills， which requires them to possess profound professional knowledge and employ narrative techniques to guide students in reflection and critical thinking， thereby improving teaching quality and learning outcomes. Future efforts should consistently deepen the connotation research of narrative education and build a systematic nursing education system.

Triptolide （TP）， the core active component of the traditional Chinese medicine Tripterygium wilfordii ， exhibits remarkable pharmacological activities including anti-inflammatory， immunosuppressive and anti-tumor effects， and holds broad application prospects in the treatment of major diseases such as autoimmune diseases and malignant tumors. However， TP has a narrow therapeutic window and causes multi-organ toxicities including liver， kidney and reproductive toxicities， which severely restrict its safe clinical application and new drug development. Therefore， toxicity reduction and efficacy enhancement has become a core scientific problem urgently to be solved in this field. This paper systematically reviews the four core strategies for TP toxicity reduction and efficacy enhancement， including structural modification， dosage form improvement， herbal compatibility， and external therapies of traditional Chinese medicine. Among them， structural modification optimizes the toxic and efficacy characteristics of TP from the molecular structure level， with typica l derivatives including （5 R ）-5-hydroxy triptolide， ZT01， PG490-88， etc. Dosage form modification achieves toxicity reduction and efficacy enhancement via targeted and sustained-controlled drug release of diverse delivery systems. It includes triptolide preparations such as nanoparticles， liposomes， microemulsion gels and liquid crystals， possessing favorable clinical transformation potential. The herbal compatibility and external therapies of traditional Chinese medicine conform to the holistic view of traditional Chinese medicine and have a profound clinical application foundation， but their mechanisms of action are insufficiently elucidated， and they lack unified standardized specifications and high-quality evidence-based proof. In the future， we should rely on multi-omics technology to elucidate the toxic and efficacy mechanisms， integrate technologies to optimize preparations， improve the evaluation system and promote clinical transformation.

ObjectiveTo investigate the value of intestinal fatty acid-binding protein （I-FABP） in predicting 6-week mortality in patients with liver cirrhosis after successful endoscopic hemostasis for esophagogastric variceal bleeding （EVB）. MethodsA retrospective analysis was performed for the clinical data of 207 patients with liver cirrhosis who underwent successful endoscopic treatment for EVB （including ligation and sclerotherapy） in The Affiliated Hospital of Yanbian University from September 2020 to June 2025， with the endpoint of 6-week bleeding-related mortality. ELISA was used to measure the serum level of I-FABP on admission， and a stratified analysis was performed based on the quartiles of I-FABP measurements. The Mann-Whitney U test was used for comparison of non-normally distributed continuous data between two groups； the chi-square test was used for comparison of categorical data between two groups. The Kaplan-Meier survival analysis， Cox regression analysis， and restricted cubic spline （RCS） curve were used to investigate the association between I-FABP and mortality. Machine learning models were used to further quantify the impact of I-FABP on mortality. The integrated Brier score and an integrated cumulative/dynamic area under the curve were used to assess the importance of time-dependent variables， and the receiver operating characteristic （ROC） curve was used to assess the performance of the predictive model. ResultsDuring the study， 29 patients （14.0%） died within 6 weeks after successful endoscopic hemostasis， with a median time to death of 16 （8—26） days. The mortality group had a significantly higher serum level of I-FABP than the survival group （Z=-3.731， P<0.001）. The Kaplan-Meier survival analysis showed that there was a significant difference in 6-week mortality between the groups of patients based on I-FABP quartiles （χ²=12.78， P=0.005）. The multivariable Cox regression analysis showed that an increase in I-FABP （hazard ratio=1.87， P=0.003） was an independent influencing factor for 6-week mortality. The RCS analysis showed a linear relationship between I-FABP and 6-week mortality （P_non-linear=0.280， P_overall=0.029）. Machine learning models showed that there was a dynamic change in the importance of I-FABP over time， and Brier score loss and the loss of cumulative/dynamic area under the curve after permutation showed that I-FABP was an important variable affecting 6-week mortality rate. ConclusionI-FABP level is independently associated with the risk of 6-week mortality endoscopic hemostasis for EVB in patients with liver cirrhosis， and therefore， it can be used as a potential biomarker for poor short-term prognosis.

OBJECTIVE To establish and verify the risk prediction models for postoperative multidrug-resistant or-ganisms(MDROs)infections in the liver transplantation patients based on the machine learning algorithms so as to provide bases for identification of the population at high risk of postoperative MDROs infections.METHODS The liver transplantation patients who were retrospectively collected from intensive care Ⅳ database(MIMIC-Ⅳ)and eICU collaborative research database(eICU)were recruited as the research subjects,meanwhile,the patients who underwent liver transplantation in the First Hospital of Shanxi Medical University from Jan.2021 to Jul.2024 were assigned as the external verification group.The variables were selected by Lasso regression,and the models were established based on 7 types of machine learning algorithms such as extreme gradient boosting algorithm and random forest.The predictive performances of the models were evaluated by comparing the areas under receiver operating characteristic(ROC)curves and the accuracy,the characteristic variables were interpreted by Shapley additive explanations(SHAP),and the risk prediction calculator was established.RESULTS A total of 637 pa-tients were finally enrolled in the study,and the incidence of postoperative MDROs infections was 35.79％.Total-ly 15 variables were finally selected for construction of the model.The area under the receiver operating character-istic curve of XGBoost model was 0.82 for the internal test set,0.78 for the external test set;the predictive per-formance of XGBoost model was better than that of the rest of 6 models.SHAP algorithm indicated that the top 5 important predictive factors were as follows:hepatic encephalopathy,length of intensive care unit(ICU)stay,albumin,model of end-stage liver disease(MELD)and total length of hospital stay.CONCLUSION The risk pre-diction models that are established based on the machine learning algorithms have remarkable effect on prediction of the postoperative MDROs infections and can accurately identify the liver transplantation patients at high risk of postoperative MDROs infections,which may provide guidance for the identification of high-risk population and the development of prevention and treatment measures for infections.

Objective To investigate the correlation between serum levels of microRNA(miR)-489-3p and miR-214-3p in patients with Psoriasis and the severity of disease.Methods From March 2022 to January 2024,138 Psoriasis patients who visited Zhangjiakou First Hospital were regarded as the study subjects(disease group).According to the psoriasis area and severity index(PASI)score,the 138 Psoriasis patients were separated into mild group(n=46),moderate group(n=54)and severe group(n=38).112 healthy individuals who underwent physical examinations in Zhangjiakou First Hospital during the same period were included in the control group.Real-time fluorescence quantitative PCR(RT-qPCR)method was applied to determine the serum levels of miR-489-3p and miR-214-3p in the subjects.The serum levels of miR-489-3p and miR-214-3p were compared between the disease group and the control group,and among patients with different degrees of disease.Spearman correlation analysis was applied to explore the relationship between serum miR-489-3p,miR-214-3p levels and disease severity in Psoriasis patients.Logistic regression analysis was performed to analyze the related factors affecting the severity of Psoriasis.Receiver operating characteristic(ROC)curve was applied to investigate the diagnostic value of serum miR-489-3p and miR-214-3p levels for severe Psoriasis.Results The serum levels of miR-489-3p(0.81±0.23)and miR-214-3p(0.79±0.22)in the disease group were lower than those in the control group(1.05±0.28,1.02±0.25),and the differences were statistically significant(t=7.441,7.732,all P<0.05).Serum miR-489-3p in mild,moderate and severe Psoriasis groups(0.93±0.24,0.80±0.23,0.69±0.22),miR-214-3p levels(0.91±0.24,0.77±0.22,0.66±0.21)decreased gradually,and the differences were statistically significant(F=12.423,13.168,all P<0.05).Spearman's results showed that serum levels of miR-489-3p and miR-214-3p were negatively correlated with the severity of Psoriasis in patients(r=-0.490,-0.463,all P<0.05).Serum miR-489-3p and miR-214-3p were independent protective factors for the severity of Psoriasis patients(Wald χ2=5.751,8.753,all P<0.05).ROC curve results showed that the area under the curve(AUC)of serum miR-489-3p and miR-214-3p for diagnosing severe Psoriasis alone was 0.785 and 0.792,with sensitivity of 78.9%and 73.7%,specificity of 49.9%and 54.7%,respectively.The AUC of the combined diagnosis for severe Psoriasis was 0.931,the sensitivity and specificity were 71.7%,71.1%,respectively,and the combined diagnostic efficacy of the two was better than that of miR-489-3p and miR-214-3p alone,and the differences were statistically significant(Z=3.018,2.773,all P<0.05).Conclusion The serum levels of miR-489-3p and miR-214-3p in patients with Psoriasis are both reduced,and both are negatively correlated with the severity of the disease in Psoriasis patients.The combined determination of the two has high efficacy in the diagnosis of severe Psoriasis.

BACKGROUND:Three-dimensional(3D)Motion Capture Technology can build accurate,objective,and quantized medical virtual simulation model,which is conducive to clinical learners'precise and in-depth understanding and mastery of various traditional therapies.The virtual simulation model of traditional Chinese medicine based on the 3D Motion Capture Technology has been reported,but such a system of traditional Mongolian medicine therapy has not been reported.OBJECTIVE:To construct an interactive 3D visualization virtual simulation model based on the 3D Motion Capture Technology.METHODS:Motion capture data of the professor of Mongolian Medicine Department were collected using the 3D optical motion capture system(Motion Analysis)and Plantar Force Platform.The 3D motion model of brain vibration therapy was constructed using Motion Builder software,and the role model was constructed using Maya software matched with the action model.Unity3D software was used to build a virtual simulation system of Mongolian medical brain vibration therapy.The system integrated information on 3D animation,kinematic and dynamic parameters of Mongolian medical brain vibration therapy.RESULTS AND CONCLUSION:By using 3D Motion Capture Technology and Computer Simulation Technology to reconstruct the operation of Mongolian medical brain vibration therapy,it can display the posture of the operator and subject and record the key parameters of spatial position and changes of joint motion to obtain kinematic and dynamic parameters.The interactive 3D virtual simulation technology is used to realize the visual presentation of 3D virtual simulation of Mongolian medical brain vibration therapy.It lays a foundation for the standardization,digitization and visualization of Mongolian medical brain vibration therapy.

This study was aimed at understanding the resistance status of dairy cow-derived Streptococcus strains in China,and providing scientific guidance for the rational use of antimicrobials and the development of new antimicrobials.Meta-analysis was used to explore the resistance of Streptococcus strains to 20 antimicrobials between 2000 and 2023.A total of 67 articles de-scribing 3 154 strains were included after a literature search,and a meta-analysis was conducted on the overall collection area according to time subgroups for 20 antimicrobials.Streptococci of dairy origin in China showed varying resistance rates(≥30％),as follows:penicillin(60％,95％CI=0.48-0.72),streptomycin(57％,95％CI=0.46-0.68),cotrimoxazole(56％,95％CI=0.28-0.82),lincomycin(51％,95％CI=0.26-0.76),tetracycline(49％,95％CI=0.40-0.59),doxycyc-line(42％,95％CI=0.24-0.60),clindamycin(41％,95％CI=0.28-0.54),ampicillin(39％,95％CI=0.27-0.52),e-rythromycin(37％,95％CI=0.28-0.45),kanamycin(36％,95％CI=0.20-0.54),and amoxicillin(30％,95％CI=0.10-0.53).On the basis of findings in the collection area,the resistance rates of dairy cow-derived Streptococcus to antimicrobials in Northeast China and Southwest China was generally high.The resistance rates of Streptococcus from dairy cattle to antimi-crobial drugs such as tetracycline,doxycycline,and lincomycin increased significantly over time.However,the resistance rates to antimicrobial drugs such as streptomycin,gentamicin,and enrofloxacin showed a significant decreasing trend.Dairy cow-de-rived Streptococcus had high resistance to some antimicrobials,and the resistance varied by region,because of differences in breeding and management.Monitoring of antimicrobial resistance rates,enhancing research on resistance mechanisms,and reg-ulating the use of antimicrobials remain necessary.

OBJECTIVE To establish and verify the risk prediction models for postoperative multidrug-resistant or-ganisms(MDROs)infections in the liver transplantation patients based on the machine learning algorithms so as to provide bases for identification of the population at high risk of postoperative MDROs infections.METHODS The liver transplantation patients who were retrospectively collected from intensive care Ⅳ database(MIMIC-Ⅳ)and eICU collaborative research database(eICU)were recruited as the research subjects,meanwhile,the patients who underwent liver transplantation in the First Hospital of Shanxi Medical University from Jan.2021 to Jul.2024 were assigned as the external verification group.The variables were selected by Lasso regression,and the models were established based on 7 types of machine learning algorithms such as extreme gradient boosting algorithm and random forest.The predictive performances of the models were evaluated by comparing the areas under receiver operating characteristic(ROC)curves and the accuracy,the characteristic variables were interpreted by Shapley additive explanations(SHAP),and the risk prediction calculator was established.RESULTS A total of 637 pa-tients were finally enrolled in the study,and the incidence of postoperative MDROs infections was 35.79％.Total-ly 15 variables were finally selected for construction of the model.The area under the receiver operating character-istic curve of XGBoost model was 0.82 for the internal test set,0.78 for the external test set;the predictive per-formance of XGBoost model was better than that of the rest of 6 models.SHAP algorithm indicated that the top 5 important predictive factors were as follows:hepatic encephalopathy,length of intensive care unit(ICU)stay,albumin,model of end-stage liver disease(MELD)and total length of hospital stay.CONCLUSION The risk pre-diction models that are established based on the machine learning algorithms have remarkable effect on prediction of the postoperative MDROs infections and can accurately identify the liver transplantation patients at high risk of postoperative MDROs infections,which may provide guidance for the identification of high-risk population and the development of prevention and treatment measures for infections.