OBJECTIVE To explore the transformation of the dispensing and drug pickup process in traditional Chinese medicine pharmacy （TCM Pharmacy） in our hospital based on data-intelligence-driven， aiming to improve pharmacists’ work efficiency and patients’ drug pickup experience. METHODS Value stream mapping and journey mapping were used to systematically identify non-value-added links in pharmacists’ dispensing process and key pain points in patients’ drug pickup under the traditional process. An intelligent dispensing and drug pickup system for the TCM Pharmacy was developed based on the C# and Android television platforms， and a machine-learning model was adopted to predict patients’ drug pickup waiting time. A comprehensive evaluation was performed from three perspectives： system performance， prediction accuracy， and satisfaction of pharmacists and patients. RESULTS The system successfully streamlined non-value-added links such as “waiting for writing on the board” and “searching for drugs”， and realized multimodal dynamic prompts of dispensing status through auditory （number calling） and visual （television terminal） channels. The constructed model for predicting drug pickup waiting time exhibited good fitting degree and generalization ability （mean absolute error＝4.28 min， R 2 ＝0.882）. The comprehensive satisfaction scores of pharmacists and patients in the traditional mode were significantly increased from （70.99±1.74） and （73.58±1.98） to （90.02±1.30） and （88.61±2.08） in the new system， respectively （ P ＜0.01）. CONCLUSIONS The transformation of the intelligent drug dispensing and pickup system for TCM pharmacy based on data-intelligence-driven effectively improves the efficiency of pharmacists’ dispensing work， realizes process transparency and waiting time predictability， and significantly enhances patients’ drug pickup experience.

ObjectiveTo develop a full-process data platform of renal rehabilitation, diagnosis and quality control information. MethodsA hierarchical architectural design was proposed, adhering to clinical pathway models and standardized data protocols. The platform comprehensively covered assessment, intervention, follow-up and quality control for maintenance hemodialysis (MHD) patients. By integrating multidisciplinary resources and standardizing rehabilitation workflows, it delivered standardized and intelligent rehabilitation services. ResultsThe platform achieved standardized and intelligent management of rehabilitation services, effectively improved the physiological function, psychological state and quality of life convenience for MHD patients, while significantly reduced the economic and care burden on patients' families and society. ConclusionThe rehabilitation service model based on a full-process data platform may provide scientific and systematic support for MHD patients.

OBJECTIVE To establish a scientific， systematic， multi-dimensional performance management system for pharmacy practice， so as to improve the efficiency and quality of pharmacy practice performance management in public hospitals. METHODS Based on the four dimensions of the balanced scorecard theory， finance， customer， internal process， learning and growth， reference indicators for pharmacy practice performance management were summarized. The Delphi method was used to screen indicators， and the analytic hierarchy process was applied to determine the weights of indicators. A pharmacy practice performance management system was then constructed. Based on this system， action plans were formulated and implemented. The effectiveness was evaluated from two aspects： customer reviews and changes in pharmacy practice outcomes. RESULTS A total of 28 reference indicators were summarized， and a performance management system for pharmacy practice was constructed， consisting of 4 primary indicators， 9 secondary indicators， and 20 tertiary indicators. Compared with action plans implementation before， the satisfaction of clinical departments was significantly improved， and 11 pharmacy practice performance management indicators were optimized after implementation. CONCLUSIONS A scientific and systematic performance management system for pharmacy practice has been successfully established， which can provide a reference for the innovation of hospital pharmacy practice management and the high quality development of pharmacy practice.

The digitization of traditional Chinese medicine (TCM) has generated vast amounts of data. However, these data are characterized by significant heterogeneity and complex semantic structures, posing substantial challenges for systematic integration and intelligent analysis, and limiting its potential for modern clinical and computational research. To address the challenges posed by the high heterogeneity and complex structure in TCM data, we designed and developed the TCM Data Hub platform, which is powered by the YiYuan large language models (LLMs). This platform aims to enhance intelligent data processing capabilities and unlock the potential for clinical application of TCM data through systematic integration and efficient utilization, thereby bridging the gap between traditional knowledge and modern computational research. This study first analyzed the heterogeneity and complexity of TCM information with respect to data types, structures, and semantics. A standardized data framework was constructed to enhance data integration and interoperability. Based on the TCM Intelligent Computing Platform of the China Academy of Chinese Medical Sciences, we trained the YiYuan LLMs to acquire domain-specific semantic understanding of TCM, thereby improving the platform’s comprehension of specialized terminology and knowledge systems. Leveraging the natural language processing capabilities of the LLMs, we developed a human-in-the-loop data processing system to enable efficient extraction, cleansing, and structured organization of TCM data. In addition, utilizing Vue and Java technologies, we developed multiple LLM-powered intelligent agents and systems, including a human-in-the-loop data processing system, as well as automated prescription mining and network pharmacology analysis agents. Task-specific agents tailored to TCM data processing were developed to enhance the model’s effectiveness in clinical knowledge discovery. System functionality and platform infrastructure were implemented using Java and Vue technologies.The TCM Data Hub platform has completed system construction and core functionality implementation. It supported integrated management and efficient access to 8 key types of TCM data: prescriptions, materia medica, ingredients, targets, diseases (Western medicine), diseases (TCM), syndromes, and therapeutic methods. The human-in-the-loop data processing system achieved an accuracy of 95.34% in structuring TCM data and supported annotation for data requiring manual labeling. The intelligent agent-driven big-data analytics module enabled 1-click, end-to-end workflows for TCM prescription mining, herb-syndrome association analysis, network pharmacology, and molecular biology research, completing a full data mining task in approximately 30 minutes. Users can interact with and manipulate data through a visual front-end interface. The system demonstrated stable performance, strong scalability, and a user-friendly experience. Empowered by the YiYuan LLMs, the TCM Data Hub platform significantly improves the accessibility, usability, and intelligence of TCM data. It effectively bridges traditional TCM knowledge with modern intelligent technologies, providing robust data support and intelligent tools for TCM research and clinical applications.

The efficacy of preoperative neoadjuvant chemoradiotherapy(nCRT)in locally advanced rectal cancer(LARC)is predicted using radiomic features of the target areas in radiotherapy for rectal cancer and an interpretable machine learning model.The clinical data are collected from 290 LARC patients who are divided into effective and ineffective groups based on tumor regression grade.The extracted radiomic features and clinicopathological data are used to develop prediction models.The optimal model is determined based on AUC performance evaluation,and the explanatory analysis is conducted using nomogram and decision curve.A total of 223 patients are included in the study,with 48 in the effective group.There are 156 patients in the training set(34 in the effective group)and 67 patients in the validation set(14 in the effective group).The nomogram model shows the best performance,with AUC of 0.858 in the training set and 0.844 in internal test set,and decision curve analysis demonstrated its superior net clinical benefit across most threshold ranges than other models.Combining radiomics and clinical variables,the nomogram can effectively predict nCRT outcomes and support clinical decision-making.

Alzheimer's disease(AD)is a chronic neurodegenerative disease that severely affects the quality of life of the elderly.Its main pathological features include the deposition of β-amyloid protein to form senile plaques,neurofibrillary tangles caused by abnormal phosphorylation of tau pro-tein,as well as extensive neuronal loss and synaptic dysfunction.In recent years,mesenchymal stem cells(MSCs)and their exosomes(MSC-Exos)have attracted extensive attention due to their poten-tial in the treatment of neurodegenerative diseases.MSCs possess multidirectional differentiation po-tential,immunomodulatory capacity,and significant neuroprotective and repair effects.As an impor-tant signaling mediator of MSCs,MSC-Exos are a type of nanoscale double-layer membrane-structured vesicles secreted by MSCs,capable of carrying and delivering various bioactive substances.MSCs and their derived MSC-Exos have demonstrated good safety and efficacy in the treatment of AD.This arti-cle systematically reviewed the basic and translational research progress on MSCs and MSC-Exos in the treatment of AD in recent years.

Objective:To compare knowledge graphs (KGs) constructed from standardized clinical pathways and actual examination records within 24 hours of emergency care for acute gastrointestinal hemorrhage (AGH), acute myocardial infarction (AMI), and intracerebral hemorrhage (ICH), and to visually analyze discrepancies between guideline recommendations and real-world practice, thereby exploring a novel methodology for clinical pathway optimization.Methods:KGs were developed using clinical pathway standards and actual examination data collected within the first 24 hours of emergency treatment for AGH, AMI, and ICH. Entity attributes were weighted to visually represent the frequency and extent of examination usage through variable node sizes in the KG. The constructed KGs were used to compare and analyze the differences in type and frequency of examinations performed relative to pathway standards.Results:The proportion of examination items with >50% adherence to clinical pathway standards within 24 hours was 76.92% for AGH, 44.44% for AMI, and 78.57% for ICH. Items from the clinical pathways that were not performed in over 50% of patients accounted for 15.38%, 27.78%, and 21.43% of cases, respectively. Non-pathway examinations increased by 9, 7, and 4 items for each condition, of which 17 items (85%) were performed at least once in more than half of the patients. Visualization via KGs revealed a reduction in redundant examinations by 38.64% between AGH and AMI, 35.00% between AGH and ICH, and 37.50% between AMI and ICH. Overall, a 54.84% reduction in redundant examinations was achieved across all three critical conditions.Conclusions:The visual KG approach effectively integrates both guideline-recommended and experience-driven examinations, serving as a correlational analysis tool to assess deviations between actual clinical practice and standardized pathways. It provides a quantitative foundation for optimizing clinical pathways, with potential for greater efficiency gains as more critical conditions are incorporated into the graph.

Objective To investigate the effects of kaempferol on the oxidative damage and apoptosis of human lens epithelial cells induced by hydrogen peroxide(H2O2),as well as its regulatory role in the Janus kinase 2/signal transducer and activator of transcription 3(JAK2/STAT3)signaling pathway.Methods Human lens epithelial cells HLE-B3 were cultured in vitro and divided into the blank group(no intervention),the model group(400 pmol?L-1 H2O2),the kaempferol group(400 μmol?L-1 H2O2+40 pmol?L-1 kaempferol),the AG490 group(400 pmol?L-1 H2O2+50 μmol?L-1 JAK2/STAT3 signaling pathway inhibitor AG490),the inhibitor group(400 pmol?L-1 H2O2+40 pmol?L-1 kaempferol+50 μmol?L-1 AG490),and the activator group(400 pmol?L-1 H2O2+40 pmol?L-1 kaempferol+0.5 μmol?L-1 JAK2/STAT3 signaling pathway activator C-A1).After 24 h of intervention,Hoechst 33258 staining was used to determine the ap-optosis rate of these cells.Malondialdehyde(MDA)and superoxide dismutase(SOD)kits were used to detect the levels of MDA and SOD.The protein expression levels of Cysteine aspartic protease 3(Caspase-3),B-cell lymphoma-2(Bcl-2),JAK2,STAT3,p-JAK2,and p-STAT3 were detected by Western blot.Results Compared with the blank group,the apop-tosis rate,the MDA level,and the protein expression levels of Caspase-3,p-JAK2,and p-STAT3 increased(all P＜0.05)in the model group,while the protein expression levels of SOD and Bcl-2 decreased(all P＜0.05).Compared with the model group,the apoptosis rate,the MDA level,and the protein expression levels of Caspase-3,p-JAK2,and p-STAT3 decreased in the kaempferol and AG490 groups(all P＜0.05),while the protein expression levels of SOD and Bcl-2 increased(all P＜0.05).Compared with the kaempferol group,the apoptosis rate,the MDA level,and the protein expression levels of Caspase-3,p-JAK2,and p-STAT3 decreased in the inhibitor group,while the protein expression levels of SOD and Bcl-2 in-creased(all P＜0.05);the changes in the above indicators in the activator group were opposite to those in the inhibitor group(all P＜0.05).Conclusion Kaempferol can protect HLE-B3 cells from H2O2-induced oxidative damage and inhibit their apoptosis by inhibiting JAK2/STAT3 signaling pathway.

Objective To investigate the association between the variability of remnant cholesterol inflammatory index(RCII),a novel composite biomarker,and the risk of stroke,in order to provide a theoretical basis for stroke prevention.Methods A prospective cohort study was conducted on 38 659 Kailuan individuals who took annual physical examinations in 2006,2008,and 2010.These subjects were grouped based on the quartiles of RCII variability,which was represented by standard deviation(SD)and average real variability(ARV),and were followed up every 2 years,with the occurrence of stroke(including ischemic and hemorrhagic strokes),death,or the end of follow-up on December 31,2022 as the endpoints.Kaplan-Meier method was used to calculate the cumulative incidence rate of endpoint events across different groups,and log-rank test was used to compare the difference of cumulative incidence of endpoint events in each group.Multivariate Cox proportional hazards regression model was adopted to analyze the association between RCII variability and risk of stroke.Results Among the 38 659 participants,a total of 2 539 strokes occurred during a mean follow-up period of 11.22±2.26 years.After adjusting confounding factors,when the participants were grouped by the quartiles of RCII-SD,the hazard ratio(HR)for stroke was 1.034(95%CI:0.917～1.167,P=0.584),1.146(95%CI:1.018～1.290,P=0.025),and 1.209(95%CI:1.066～1.370,P=0.003),respectively in the Q2,Q3,and Q4 groups,when compared with the Q1 group(Ptrend<0.05).When they were grouped by the quartiles of RCII-ARV,the HR for stroke was 1.008(95%CI:0.894～1.136,P=0.901),1.109(95%CI:0.986～1.248,P=0.085),and 1.152(95%CI:1.018～1.303,P=0.025),respectively,in the Q2,Q3,and Q4 groups,when compared with the Q1 group.Furthermore,both sensitivity and stratified analyses yielded similar results.Conclusion RCII variability is significantly associated with stroke,and the risk of stroke is gradually increasing with increment of the variability.Countermeasures Relevant authorities can focus on reducing RCII variability as a central objective by establishing regular monitoring mechanism,strengthening lifestyle interventions,and standardizing dietary,exercise,and weight management in order to suppress the index fluctuations.The principle of stable lipid-lowering in medication and optimization of therapeutic regimens with stable efficacy should be emphasized to prevent the risk of additional vascular damage.

Objective To explore the clinical application value of gadolinium ethoxybenzyl diethylenetriamine pentaacetic acid(Gd-EOB-DTPA)enhanced MRI T1 mapping in the evaluation of liver function.Methods Sixty-four patients who underwent enhanced MRI T1 mapping with Gd-EOB-DTPA and completed the laboratory examination of liver function within one week were prospectively enrolled.All patients were divided into normal control group(NCG),cirrhosis Child-Pugh A(CCA)group,cirrhosis Child-Pugh B(CCB)group,and cirrhosis Child-Pugh C(CCC)group.CCB+CCC groups were defined as a moderate and severe abnormal liver function group.The T1 mapping images of pre-enhanced,post-enhanced 10 min and 20 min were collected,and the T1 mapping val-ues of liver and spleen were measured.The ΔT1 and hepatocyte enhancement fraction(HEF)were calculated.The differences of parameters in different liver function groups were analyzed and compared,and the diagnostic efficacy of each index in distinguishing different liver function groups was evaluated.Results There were significant differences in T1plain scan,T110 min,T120 min,ΔT110 min,ΔT120 min,HEF10 min and HEF20 min among the three groups(P<0.05).The difference of T1plain scan between NCG and CCA groups,and between NCG and CCB+CCC groups was statistically significant(P<0.05).The area under the curve(AUC)of differentiating normal liver function group from abnormal liver function group was 0.761.There were significant differences in T110 min,T120 min,ΔT110 min,ΔT120 min,HEF10 min and HEF20 min between CCA and CCB+CCC groups.The AUC of differentiating the two groups was 0.757,0.820,0.735,0.820,0.790 and 0.853,respectively,and HEF20 min had the highest diagnostic efficacy.Conclusion Gd-EOB-DTPA enhanced MRI T1 mapping can be used as an effective method to evaluate liver function.