ObjectiveTo construct and validate a clinical prediction model for Qi deficiency and blood stasis syndrome in chronic heart failure （CHF），aiming to assist clinical diagnosis and provide tools and methods for individualized treatment of CHF. MethodsThe clinical data of patients with chronic heart failure treated at Dongzhimen Hospital of Beijing University of Chinese Medicine from January 2022 to January 2024 were retrospectively collected. The patients were randomly divided into a training group and a validation group with a ratio of 7∶3. First， the least absolute shrinkage and selection operator （LASSO） regression analysis was used to preliminarily screen the predictive factors affecting the diagnosis of Qi deficiency and blood stasis syndrome in CHF. Subsequently， the Logistic regression method was applied to conduct a more in-depth and detailed analysis of these factors. Variables with P<0.05 in the results of the multi-factor Logistic regression were carefully selected and included. Based on the regression coefficients obtained from this analysis， a model was constructed， and a nomogram was accurately drawn. Using R software，the receiver operating characteristic （ROC） curve，calibration curve，and decision curve analysis （DCA） were precisely drawn. These analyses were used to comprehensively evaluate the model from three crucial aspects： discrimination，calibration，and clinical applicability. Additionally， the accuracy，specificity，sensitivity，positive predictive value，and negative predictive value of the model were meticulously calculated to conduct a more all-round and comprehensive assessment. ResultsIn total， 168 cases were successfully obtained in the training group， and 71 cases were included in the validation group. After a thorough comparison， it was found that there were no statistically significant differences in the baseline data between the two groups. After being rigorously screened by the LASSO-multivariate logistic regression method， dark red tongue，smoking history，cardiac troponin I，and N-terminal pro-B-type natriuretic peptide （NT-ProBNP） were identified as the influencing factors for diagnosing patients with the Qi deficiency and blood stasis syndrome in CHF. The constructed model demonstrated an area under the curve （AUC） of 0.812 in the training group and 0.719 in the validation group. The calibration curve showed that the predicted curve of the model was close to the actual observed curve. DCA indicated that the model could provide substantial clinical benefits for patients at the decision thresholds ranging from 0.2 to 0.9. ConclusionThe clinical prediction model for Qi deficiency and blood stasis syndrome in chronic heart failure constructed in this study shows good performance. It has certain application value in clinical practice， which may contribute to the improvement of the diagnosis and treatment of CHF patients with this syndrome.

ObjectiveStarting from the etiology， pathogenesis， and treatment strategies of endometriosis and adenomyosis， to integrate and sort out the academic characteristics of contemporary renowned experts and schools in the field of traditional Chinese medicine gynecology. MethodsAccording to the systematic review of text and opinion （SrTO） process developed by the Joanna Briggs Institute （JBI） in Australia， this paper determined literature screening criteria by searching China National Knowledge Infrastructure （CNKI）， VIP， Wanfang， and China Biomedical Literature Database. Information was extracted after literature screening， and quality evaluation was conducted using the JBI Narrative， Text， and Opinion Systematic Review Strict Evaluation Checklist. The JBI Narrative， Opinion， Text Evaluation， and Review Tool Summary Table was used for information synthesis， and data analysis and display were conducted in the form of text and charts. ResultsThe 146 articles related to 39 renowned experts and 19 articles related to 10 schools of thought were included. Research has found that contemporary experts and schools in traditional Chinese medicine gynecology consider blood stasis as the core pathogenesis in understanding the etiology and pathogenesis of two diseases and related infertility. Their viewpoints varied from multiple aspects such as clinical symptom characteristics， meridian circulation location， pathological product evolution， disease duration， emotional psychology， lifestyle habits， preference for food and drink， innate endowment， and acquired injury. In terms of treatment， it was advocated to divide the stage， treat according to different types， adapt to the times， integrate nature and humans， and combine multiple methods to treat comprehensively when necessary. It was also recommended to skillfully use insects， make good use of classic formulas and small prescriptions， pay attention to protecting the spleen and stomach and regulating emotions， and make good use of self-formulated empirical formulas for internal or external use. Besides， individualized long-term management of patients was also advocated. ConclusionThis study applies the SrTO process to systematically summarize the academic ideas of contemporary renowned experts and schools in traditional Chinese medicine gynecology regarding the causes， mechanisms， diagnosis， and treatments of endometriosis， providing a scientific and standardized reference for future theoretical exploration.

ObjectiveTo develop a predictive model and application for spontaneous passage of common bile duct stones using automated machine learning algorithms given the complexity of treatment decision-making for patients with common bile duct stones， and to reduce unnecessary endoscopic retrograde cholangiopancreatography （ERCP） procedures. MethodsA retrospective analysis was performed for the data of 835 patients who were scheduled for ERCP after a confirmed diagnosis of common bile duct stones based on imaging techniques in Changshu First People’s Hospital （dataset 1） and Changshu Traditional Chinese Medicine Hospital （dataset 2）. The dataset 1 was used for the training and internal validation of the machine learning model and the development of an application， and the dataset 2 was used for external testing. A total of 22 potential predictive variables were included for the establishment and internal validation of the LASSO regression model and various automated machine learning models. The area under the receiver operating characteristic curve （AUC）， sensitivity， specificity， and accuracy were used to assess the performance of models and identify the best model. Feature importance plots， force plots， and SHAP plots were used to interpret the model. The Python Dash library and the best model were used to develop a web application， and external testing was conducted using the dataset 2. The Kolmogorov-Smirnov test was used to examine whether the data were normally distributed， and the Mann-Whitney U test was used for comparison between two groups， while the chi-square test or the Fisher’s exact test was used for comparison of categorical data between groups. ResultsAmong the 835 patients included in the study， 152 （18.20%） experienced spontaneous stone passage. The LASSO model achieved an AUC of 0.875 in the training set （n=588） and 0.864 in the validation set （n=171）， and the top five predictive factors in terms of importance were solitary common bile duct stones， non-dilated common bile duct， diameter of common bile duct stones， a reduction in serum alkaline phosphatase （ALP）， and a reduction in gamma-glutamyl transpeptidase （GGT）. A total of 55 models were established using automated machine learning， among which the gradient boosting machine （GBM） model had the best performance， with an AUC of 0.891 （95% confidence interval： 0.859‍ ‍—‍ ‍0.927）， outperforming the extreme randomized tree mode， the deep learning model， the generalized linear model， and the distributed random forest model. The GBM model had an accuracy of 0.855， a sensitivity of 0.846， and a specificity of 0.857 in the test set （n=76）. The variable importance analysis showed that five factors had important influence on the prediction of spontaneous stone passage， i.e.， were solitary common bile duct stones， non-dilated common bile duct， a stone diameter of <8 mm， a reduction in serum ALP， and a reduction in GGT. The SHAP analysis of the GBM model showed a significant increase in the probability of spontaneous stone passage in patients with solitary common bile duct stones， non-dilated common bile duct， a stone diameter of <8 mm， and a reduction in serum ALP or GGT. ConclusionThe GBM model and application developed using automated machine learning algorithms exhibit excellent predictive performance and user-friendliness in predicting spontaneous stone passage in patients with common bile duct stones. This application can help avoid unnecessary ERCP procedures， thereby reducing surgical risks and healthcare costs.

OBJECTIVE To systematically investigate the current status and effectiveness of the standardized on-the-job training program for community clinical pharmacists in Shanghai， and to provide a scientific basis for optimizing the training scheme. METHODS A questionnaire survey was conducted to collect the data from trainees and mentor pharmacists who participated in the program between 2016 and 2024. The survey examined their basic information， evaluations of the training scheme， satisfaction with training outcomes， and suggestions for improvement. Statistical analyses were also conducted. RESULTS A total of 420 valid responses were collected， including 340 from trainees and 80 from mentor pharmacists. Before training， only 30.29% of trainees were engaged in clinical pharmacy-related work， whereas this proportion increased to 73.24% after training. Most mentor pharmacists had extensive experience in clinical pharmacy （76.25% with ≥5 years of experience） and mentoring （78.75% with ≥3 teaching sessions）. Totally 65.59% of trainees and 55.00% of mentor pharmacists believed that blended training yielded the best learning outcomes. Over 80.00% of both trainees and mentor pharmacists considered the overall training duration， theoretical study time， and practical training time to be reasonable. More than 95.00% of trainees and mentor pharmacists agreed that the homework and assessment schemes were appropriate. Trainees rated the relevance of training content to their actual work highly （with an average relevance score ＞4.5）， though they perceived the chronic disease medication therapy management module as significantly more challenging than the prescription review and evaluation module and the home-based pharmaceutical care module. The average satisfaction score of trainees and mentor pharmacists with the training effectiveness of each project was above 4 points， indicating a high overall satisfaction. Inadequate provision of teaching resources was unanimously recognized by trainees and mentor pharmacists as the key area requiring improvement. CONCLUSIONS The standardized on-the-job training program for community clinical pharmacists in Shanghai has contributed to improving pharmaceutical services in community healthcare settings. However， ongoing improvements must concentrate on content design， resource development， and faculty cultivation.

Objective To explore the association of working hours and shift work with occupational stress, fatigue accumulation, and depressive symptoms among primary community medical workers. Methods A total of 516 medical workers from five community medical service centers in Pudong New Area, Shanghai City, were selected as the research subjects using the convenience sampling method. The Core Scale of Occupational Stress Measurement, the Workers' Fatigue Accumulation Self-diagnosis Questionnaire, and the Patient Health Questionnaire were used to assess research subjects' occupational stress, fatigue accumulation, and depressive symptoms, respectively. Results Long working hours (>40 hours/week) were reported by 50.4% of workers among the research subjects, while shift works were reported by 16.9% of the workers. The detection rates of occupational stress, fatigue accumulation, and depressive symptoms were 26.6%, 41.7%, and 30.8%, respectively. Multivariate logistic regression analysis result revealed that, after adjusting for confounders such as age, sex, and education level, longer working hours were associated with higher risks of occupational stress, fatigue accumulation, and depressive symptoms (all P<0.05). Shift workers in community medical centers had higher risks of occupational stress, fatigue accumulation, and depressive symptoms compared with non-shift workers (all P<0.05). Conclusion Long working hours and shift work could increase the risks of occupational stress, fatigue accumulation, and depressive symptoms among community medical workers.

With the rapid advancement of artificial intelligence technology, chatbots have shown great potential in the healthcare sector. From personalized health advice to chronic disease management and psychological support, chatbots have demonstrated significant advantages in improving the efficiency and quality of healthcare services. As the scope of their applications expands, the relationship between technological complexity and practical application scenarios has become increasingly intertwined, necessitating a more comprehensive evaluation of both aspects. This paper, from the perspective of he althcare applications, systematically reviews the technological pathways and development of chatbots in the medical field, providing an in-depth analysis of their performance across various medical scenarios. It thoroughly examines the advantages and limitations of chatbots, aiming to offer theoretical support for future research and propose feasible recommendations for the broader adoption of chatbot technologies in healthcare.

Objective:To explore the application effects of the goal-oriented teaching method based on mind mapping in the teaching of stomatology practical courses.Methods:From September 2022 to September 2023, 52 fourth-year students of clinical stomatology at Harbin Medical University were divided into test group and control group for practical teaching, with 26 cases in each group. The test group received goal-oriented teaching based on mind mapping, while the control group received traditional teaching, for 20 class hours in both groups. The two groups were compared in terms of general data, theoretical and practical assessment scores, the score of the self-rating scale of self-directed learning (SRSSDL) and the score of critical thinking disposition inventory-Chinese version (CTDI-CV) before and after training, and student satisfaction with teaching activities. SPSS 25.0 software was used to perform the t-test or χ2 test. Results:After completing the practical training courses, the test group showed significantly higher scores than the control group in multiple-choice questions [(16.85±1.39) vs. (15.33±2.21)], fill-in-the-blank questions [(17.21±1.98) vs. (16.01±2.02)], short answer questions [(17.47±2.27) vs. (15.23±2.45)], case analysis [(34.36±2.79) vs. (32.57±3.02)], and practical assessment [(84.69±4.73) vs. (80.57±4.21)] (all P<0.05). The SRSSDL score and CTDI-CV score were improved in both groups, and were significantly higher in the test group [(215.29±10.42) and (357.49±17.80)] than in the control group [(200.23±11.42) and (342.23±17.26)] (both P<0.05). The students of the test group were significantly more satisfied with teaching activities than those of the control group ( P<0.05). Conclusions:Compared with the traditional teaching method, the goal-oriented teaching method based on mind mapping is more effective in stomatology practical teaching, which can improve students' self-directed learning ability and critical thinking ability, promote their mastery of theoretical knowledge, enhance their clinical practice ability, and increase their satisfaction with teaching activities.

Objective:To investigate the influence of different test conditions on the particle size distribution of elemene emulsion injection measured by laser light scattering method.Methods:The method of particle size deter-mination of elemene emulsion injection was explored.The test conditions were as follows:shading rate 5％-10％,absorption rate 0.000 1-0.1,refractive index1.52-1.54,mixing speed 800-1 600 r·min-1,balance time 0.5-1 min.After the methodology verification,3 batches of elemene emulsion injection were taken and deter-mined on the Bettersize 2600 laser particle size distribution instrument(wet method).Results:Measurement results of 3 batches of samples:d(0.1),d(0.5),d(0.9),d(0.99)were 252,251,213 nm;354,351,316 nm;543,532,476 nm;979,953,887 nm.Conclusion:This test method can be used to determine the particle size distribution of elemene emulsion injection with good reproducibility.

AIM:To study the effect of hepatitis B combined with hepatic fibrosis on endogenous and exogenous metabolism of liver and the effect of glycyrrhizic acid combined with tenofovir(TFV)es-ter on anti-HBV efficacy.METHODS:Hepatitis B mouse was induced by chronic CCI4 to form a mod-el of hepatitis B with hepatic fibrosis.H&E staining,Sirius Red Staining,α-SMA immunohistochemistry were used to detect pathological changes in liver tissue.The changes of liver endogenous metabo-lism in mice with hepatitis B and hepatic fibrosis were detected by metabolomics.LC-MS/MS was used to investigate the plasma and liver concentra-tions of TFV and its active metabolite(TFV-DP),for investigating the changes of exogenous metabo-lism.RESULTS:HBV+CCl4 mice showed fibrosis symptoms such as liver injury and collagen deposi-tion.Hepatitis B combined with hepatic fibrosis af-fected nucleotide metabolism,amino acid metabo-lism,tricarboxylic acid cycle,pentose phosphate pathway and other endogenous metabolism,low-ered the hepatic level of TFV-DP,and decreased the antiviral efficacy.By combining with glycyrrhizic acid or forming a self-assembled preparation,the hepatic level of TFV-DP was improved,and the anti-viral efficacy was enhanced.CONCLUSIONS:Hepati-tis B combined with hepatic fibrosis affected both endogenous and exogenous metabolism of liver.Different forms of combination of glycyrrhizic acid and TFV could elevate the level of TFV-DP in liver and improve the antiviral efficacy in HBV+CCI4 mice.

Bovine leukemia virus(BLV)mainly causes bovine B-cell malignant lymphoma,which causes immunosuppression and leads animals susceptible to other diseases.BLV has been detected all over the world except in Western Europe.Antibodies to BLV have been detected in humans,and reverse transcribed DNA of BLV were detected in breast tissue sections and lung tumors,which in-dicate that BLV is a potential zoonotic disease.At present,there are no effective treatment methods or commercial vaccines for BLV.An in-depth understanding of the development of BLV detection technology will help researchers choose suitable detection methods,avoid invalid detection results,and meet the requirements of disease prevention and control.In view of this,this paper reviews 19 detection technologies of BLV including cytology detection,nucleic acid detection,and serology de-tection.The advantages,disadvantages,and scope of application were also analyzed,which provide theoretical guidance for the prevention and control of bovine leukemia.