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.

A 51-year-old male presented with nasal obstruction, followed by progressive hearing loss and blurred vision. Imaging identified space-occupying lesions in the paranasal sinuses, orbits, and paraspinal regions, while laboratory tests confirmed positive anti-proteinase 3 anti-neutrophil cytoplasmic antibody(PR3- ANCA) immunoglobulin G (IgG)and markedly elevated serum IgG4. Despite treatment with corticosteroids, immunosuppressants, and radiotherapy, the patient exhibited steroid dependency with relentless disease progression. Following multidisciplinary consultation, a diagnosis of inflammatory myofibroblastic tumor (IMT) coexisting with ANCA- associated vasculitis (AAV) was favored, though IgG4-related disease remained a critical differential. Ultimately, profound immunosuppression precipitated a severe herpesvirus infection, leading to disseminated intravascular coagulation and multiple organ dysfunction syndrome. This case underscores the rarity and diagnostic complexity of concurrent IMT and AAV, highlights the therapeutic dilemma of balancing primary disease control against fatal opportunistic infections, and emphasizes the critical role of multidisciplinary collaboration in the diagnosis and treatment of complex diseases.

To further improve the post competency of application-oriented medical students, the university medical simulation center, clinical teaching base, and off-campus social practice base were linked to establish a platform. Four key points were used to explore a new training model of "one body and four bases" for application-oriented medical students. This includes problem-oriented theoretical teaching to improve the professional knowledge of medical students, hands-on practice-oriented experimental teaching to improve the clinical skills, "strengthening clinical thinking training"-oriented practice in the base to enhance clinical awareness and cultivate clinical habits, and "cultivating humanistic literacy"-oriented off-campus social practice base to improve the humanistic sentiment and professional spirit of medical students. This teaching mode lays a foundation for training high-quality application-oriented medical talents with solid knowledge and skills and comprehensive development of ability and literacy, and provides a reference for teaching and research in similar colleges and universities.

As the application of immune checkpoint inhibitors(ICIs)in the perioperative treatment of melanoma is increasingly introduced at earlier stages,it presents a critical opportunity for the development and clinical translation of neoadjuvant therapy.The results of phaseⅠ/Ⅱ clinical trials on neoadjuvant ICI therapy for melanoma demonstrate that neoadjuvant ICIs effectively improve the pathologic re-sponse rate in melanoma patients.Recent studies have shown that combining ICIs with other treatment modalities,including radiotherapy,chemotherapy,and targeted therapies,can enhance antitumor efficacy of neoadjuvant treatment for patients with melanoma.Optimizing treatment regimens,managing adverse events,identifying and addressing pseudoprogression,and handling cases of oligoprogression have become key areas of research in incorporating ICI regimens into neoadjuvant treatment for patients with melanoma.The search for bio-markers to monitor immunotherapy efficacy is expected to become a major focus of future research.This article provides a review of the re-search progress,controversies,and challenges in the application of ICIs in the neoadjuvant treatment of melanoma,and discusses future re-search directions,aiming to offer insights into the clinical application and development of ICIs in melanoma neoadjuvant therapy.

Objective To explore how digital and intelligent technologies can optimize the storage allocation and picking paths for Traditional Chinese medicine decoction pieces.Methods Based on prescription information and medicine data from the hospital information system(HIS),this study employs MATLAB programming to use an integer linear programming(ILP)algorithm for optimizing the storage allocation of Traditional Chinese medicine decoction pieces.Additionally,a greedy algorithm is applied to optimize the picking paths to reduce the picking distance for pharmacists.Finally,an independent samples paired t-test is used to analyze the experimental data to verify the significance of the optimizations.Results A total of 7 734 prescriptions were collected from the HIS.The results of storage optimization showed that the total distance before optimization was(87.58±0.29)m,which was reduced to(85.35±0.28)m after optimization(P﹤0.000 1).The picking path optimization results showed that the picking path was(85.35±0.28)m before optimization and(40.06±0.11)m after optimization(P﹤0.000 1).The results of the independent samples paired t-test indicate that the path was significantly reduced after both storage and picking path optimizations,with statistical significance.Conclusion By using digital and intelligent methods,informatics pharmacists can effectively shorten the picking paths for Traditional Chinese medicine decoction pieces,improve dispensing efficiency,and reduce patient waiting times.

Objective To explore how digital and intelligent technologies can optimize the storage allocation and picking paths for Traditional Chinese medicine decoction pieces.Methods Based on prescription information and medicine data from the hospital information system(HIS),this study employs MATLAB programming to use an integer linear programming(ILP)algorithm for optimizing the storage allocation of Traditional Chinese medicine decoction pieces.Additionally,a greedy algorithm is applied to optimize the picking paths to reduce the picking distance for pharmacists.Finally,an independent samples paired t-test is used to analyze the experimental data to verify the significance of the optimizations.Results A total of 7 734 prescriptions were collected from the HIS.The results of storage optimization showed that the total distance before optimization was(87.58±0.29)m,which was reduced to(85.35±0.28)m after optimization(P﹤0.000 1).The picking path optimization results showed that the picking path was(85.35±0.28)m before optimization and(40.06±0.11)m after optimization(P﹤0.000 1).The results of the independent samples paired t-test indicate that the path was significantly reduced after both storage and picking path optimizations,with statistical significance.Conclusion By using digital and intelligent methods,informatics pharmacists can effectively shorten the picking paths for Traditional Chinese medicine decoction pieces,improve dispensing efficiency,and reduce patient waiting times.

Objective:To systematically evaluate the effect of the Dietary Approaches to Stop Hypertension (DASH) diet on common metabolic diseases.Methods:Following the PICOS framework to construct the search formula, we systematically searched the Web of science, PubMed, Cochrane Library, CNKI, Wanfang, and VIP databases for randomized controlled trials (RCTs) investigating the effect of the DASH diet on multiple metabolic indices including body weight, body mass index (BMI), fasting blood glucose, triglycerides, systolic blood pressure (SBP), and diastolic blood pressure (DBP) in patients with metabolic disorders (e.g., obesity, diabetes mellitus, and hypertension) published both in China and abroad from 1 January 2000 to 31 December 2023. The search terms were combinations of MeSH and free-text terms, and the raw data obtained from the search were screened according to the inclusion and exclusion criteria to determine the articles that were finally included in the analysis. The differences in these metabolic indices were compared between the intervention group group (using DASH diet) and the control group. The quality of the studies was assessed quantitatively using the modified Jadad scale and qualitatively using the Risk of Bias 2 (RoB 2) tool by two reviewers independently. Data analysis was conducted using Stata 18.0 software, with the I 2 test for heterogeneity evaluation and funnel plots for qualitative assessment of publication bias. Results:A total of 13 RCTs were included, involving 1 653 participants. Meta-analysis showed that the intervention group had more favorable effects on SBP ( SMD:-0.91, 95%CI: -1.55–-0.27; Z=-2.79, P<0.005) and DBP ( SMD: -0.98, 95%CI: -1.62–-0.33; Z=-2.96, P<0.05) than the control diet. Fasting blood glucose ( SMD: 0.21, 95% CI: 0.01–0.41; Z=2.06, P=0.04) was statistically significant. There were no significant differences in body weight, BMI, fasting blood glucose, and triglyceride outcomes betweeen these two groups. Conclusions:DASH diet is effective in controlling SBP and DBP in patients with metabolic disorders and may be useful in clinical adjunctive therapy. However, current evidence does not support an independent improvement in glycolipid metabolic markers.

The aim of this study is to establish a rapid,efficient,and sensitive method for detecting the infectious laryngotracheitis virus(ILTV).The DNA of ILTV was extracted and used as a tem-plate to develop a recombinant enzyme-mediated isothermal amplification(RAA)fluorescence de-tection method for ILTV through optimization of conditions,sensitivity analysis,and repeatability assessment.Additionally,the nucleic acids of avian influenza virus(AIV),IBV,and Newcastle dis-ease virus(NDV)were detected to verify the specificity of this method.Finally,this method was applied to analyze 59 clinical samples collected from multiple large-scale chicken farms in Hebei Province,and the results were compared with those obtained from real-time fluorescence quantifi-cation(qPCR)and PCR methods according to national standards.The results showed that the RAA detection method established in this study had a reaction system of 25.0 μL buffer,2.1 μL primer,0.6 μL probe,5.0 μL magnesium acetate,and 5.0 μL template.The reaction temperature was 39 ℃ and the amplification time was within 20 minutes.The sensitivity of this method was 101 copies/μL,and the specificity detection was 100％.Testing of 59 clinical samples showed that 17 were detected positive by both RAA fluorescence and qPCR,and 12 were detected by PCR,and the detection rate of RAA(fluorescence)was consistent with real-time fluorescence quantification and qPCR,which was higher than that of the PCR assay.The research results indicate that the RAA fluorescence method has a short detection time,good specificity and sensitivity,and can be used for rapid detection of ILTV.

Objective:To systematically evaluate the effect of the Dietary Approaches to Stop Hypertension (DASH) diet on common metabolic diseases.Methods:Following the PICOS framework to construct the search formula, we systematically searched the Web of science, PubMed, Cochrane Library, CNKI, Wanfang, and VIP databases for randomized controlled trials (RCTs) investigating the effect of the DASH diet on multiple metabolic indices including body weight, body mass index (BMI), fasting blood glucose, triglycerides, systolic blood pressure (SBP), and diastolic blood pressure (DBP) in patients with metabolic disorders (e.g., obesity, diabetes mellitus, and hypertension) published both in China and abroad from 1 January 2000 to 31 December 2023. The search terms were combinations of MeSH and free-text terms, and the raw data obtained from the search were screened according to the inclusion and exclusion criteria to determine the articles that were finally included in the analysis. The differences in these metabolic indices were compared between the intervention group group (using DASH diet) and the control group. The quality of the studies was assessed quantitatively using the modified Jadad scale and qualitatively using the Risk of Bias 2 (RoB 2) tool by two reviewers independently. Data analysis was conducted using Stata 18.0 software, with the I 2 test for heterogeneity evaluation and funnel plots for qualitative assessment of publication bias. Results:A total of 13 RCTs were included, involving 1 653 participants. Meta-analysis showed that the intervention group had more favorable effects on SBP ( SMD:-0.91, 95%CI: -1.55–-0.27; Z=-2.79, P<0.005) and DBP ( SMD: -0.98, 95%CI: -1.62–-0.33; Z=-2.96, P<0.05) than the control diet. Fasting blood glucose ( SMD: 0.21, 95% CI: 0.01–0.41; Z=2.06, P=0.04) was statistically significant. There were no significant differences in body weight, BMI, fasting blood glucose, and triglyceride outcomes betweeen these two groups. Conclusions:DASH diet is effective in controlling SBP and DBP in patients with metabolic disorders and may be useful in clinical adjunctive therapy. However, current evidence does not support an independent improvement in glycolipid metabolic markers.

Alzheimer's disease(AD),a neurodegenerative disorder,manifests pathological changes in the brain even during the asymptomatic stage.As the pathological burden intensifies,patients experience functional decline in multiple cognitive domains,including memory,language,spatial perception,executive function,and calculation,and may also exhibit emotional abnormalities.Once AD progresses,treatment becomes extremely chal-lenging.Therefore,early diagnosis and accurate prediction of disease conversion are core tasks in the prevention and treatment of AD,and they are also urgent scientific research challenges to be overcome.Deep learning(DL)models demonstrate considerable advantages in the diagnosis,prediction,classification,and feature extraction of AD,offering new hope for solving this challenging problem.This research commences with a concise introduction to the outcomes of AD and the fundamental knowledge of deep learning.Subsequently,it offers an overview of the imaging studies on the utilization of deep learning for predicting disease transformation from two perspectives.Firstly,it systematically summarizes the existing DL models that have demonstrated innovation in the classification and prediction performance of AD.Secondly,it provides a comprehensive outline of the DL fusion models applied to the diagnosis,classification,and prediction of AD.Finally,this paper expounds upon the impending challenges in the research of this domain.This article demonstrates that deep learning models is cutting-edge trends in the ex-ploration of AD research.