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.

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.

Alzheimer disease(AD)is a neurological disease characterized by cognitive decline.AD continuum refers to the dynamic development progression from early pathological changes to obvious clinical symptoms,covering the continuous spectrum of subjective cognition decline(SCD)stage,mild cognitive impairment(MCI)stage and dementia stage.As one of the key brain regions involved in early stage,hippocampus(HP)in AD continuum is closely related to the progression of disease.MRI has been widely used in the study of HP in the AD continuum.The progresses in structural and functional MRI research of HP changes in AD continuum were reviewed in this article.

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.

Alzheimer disease(AD)is a neurological disease characterized by cognitive decline.AD continuum refers to the dynamic development progression from early pathological changes to obvious clinical symptoms,covering the continuous spectrum of subjective cognition decline(SCD)stage,mild cognitive impairment(MCI)stage and dementia stage.As one of the key brain regions involved in early stage,hippocampus(HP)in AD continuum is closely related to the progression of disease.MRI has been widely used in the study of HP in the AD continuum.The progresses in structural and functional MRI research of HP changes in AD continuum were reviewed in this article.

The primary role of transfer RNA(tRNA)is to connect a specific amino acid to its 3' end, use its anticodon to match the codon on messenger RNA(mRNA), and deliver the corresponding amino acid to the ribosome for protein synthesis.tRNA exists in two forms: precursor tRNA and mature tRNA.When acted upon by enzymes like Dicer, elaC ribonuclease Z 2(ELAC2), angiopoietin(ANG), and other ribonucleases, tRNA is broken down into tRNA-derived stress-induced RNA(tiRNA)and tRNA-derived fragments(tRF).Recent advancements in RNA sequencing technology have led to increased interest in tiRNA and tRF, shedding light on their roles in various physiological and pathological processes.tRNA-derived small molecules(tsRNA)function similarly to microRNA(miRNA), influencing gene expression and protein synthesis.They show promise as diagnostic markers and potential therapeutic targets for age-related diseases.This review offers a comprehensive analysis of tsRNA classification, biological functions, research advancements, and clinical applications in age-related conditions.

This document targets digital human metabolic chamber platforms and specifies construction standards and testing protocols covering the full lifecycle of " build-test-operate." It encompasses chamber engineering and environmental control, digital platform and cybersecurity architecture, metabolic measurement and multimodal data acquisition, as well as quantitative system performance and data quality indicators with verifiable acceptance tests. By standardizing architecture, interfaces, and quality control, the specification enables multicenter data interoperability and harmonized quality management, providing high-quality, verifiable, and traceable infrastructure to support precision metabolism research and clinical translation in China.

Body weight abnormalities, including overweight, obesity, and underweight, have become a dual public health challenge in Chinese adults: overweight and obesity lead to a variety of chronic complications, while underweight increases the risks of malnutrition, sarcopenia, and organ dysfunction. To systematically address these issues, multidisciplinary experts in endocrinology, sports science, nutrition, and psychiatry from various regions have held multiple weight management seminars. Based on the latest epidemiological data and clinical evidence, they expanded the guideline to include assessment and intervention strategies for underweight, in addition to the core content of obesity management. This guideline outlines the etiological mechanisms, evaluation methods, and multidimensional management strategies for overweight and obesity, covering key areas such as diagnosis and assessment, medical nutrition therapy, exercise prescription, pharmacological intervention, and psychological support. It is intended to provide a scientific and standardized approach to weight management across the adult population, aiming to curb the rising prevalence of obesity, mitigate complications associated with abnormal body weight, and improve nutritional status and overall quality of life.

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.

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.