Rare diseases pose significant diagnostic and therapeutic challenges,carrying a high disease burden,their management critically reflects a nation's public health resilience.Currently,China faces key challenges such as scarce treatments,fragmented services,and low drug accessibility in rare disease care,which urgently require systemic solutions.Digital-intelligent technology as a key breakthrough are expected to resolve the challenges in this field.Although its application in the field of rare diseases is gradually expanding,there is a lack of systematic compilation of studies to elucidate how to precisely enhance the precision,synergy and sustainability of diagnosis and treatment.The key challenges in rare disease care concentrate in four areas:inefficiency in prenatal screening,uneven distribution of medical resources,low efficiency in social organization collaboration,and ineffective information dissemination.The"4C"strategy,based on digital-intelligent technology,can address these issues:①coordination,boost prenatal screening awareness and capacity via digital-intelligent platforms to strengthen prevention;②cooperation,deepen collaboration within specialist networks,empowering institutions to enhance diagnostic capacity;③co-creation,empower support organizations to optimize resources,efficiency;④cognition,minimize information dissipation through efficient platforms,improving patient and family quality of life.This establishes an integrated digital-intelligent rare disease model encompassing"screening-diagnosis-treatment-care".

With the advancement of the "New Medical Science" reform, the "Medicine+X" model has emerged as a key direction for the future development of medical education. Multidisciplinary integration places higher demands on both educators and students. Emerging technologies, such as intelligent tutoring systems, adaptive learning platforms, intelligent campus management systems, and ChatGPT, have made personalized learning possible. Such approaches offer notable advantages, including improving learning efficiency, enhancing motivation, eliminating the spatiotemporal constraints of clinical education, and alleviating teachers′ workloads. Nevertheless, the application of artificial intelligence in personalized medical education still faces multiple challenges, such as issues of data quality and reliability, the need for faculty development, shifts in educational paradigms, and ethical considerations. This study explored the current status of artificial intelligence in personalized medical education and offered recommendations to promote its development, including strengthening the integration of technology and education, enhancing the digital literacy of educators, establishing ethical guidelines, and fostering multi-stakeholder collaboration.

In traditional teaching, medical students have limited opportunities to interact with patients, which constrains the development of their clinical skills. Virtual standardized patients offer a potential solution to this limitation. This article analyzes the advantages of virtual standardized patients and their application in clinical teaching.

Objective: To analyze the status and trends of the disease burden of periodontal disease among women of reproductive age (15-49 years) in China from 1990 to 2021, and to provide a reference for the development of periodontal disease prevention and control strategies for women of reproductive age. Methods: Using the global burden of disease (GBD) data from 1990 to 2021, this study investigated the periodontal disease burden among women of reproductive age, including prevalence, incidence, disability-adjusted life years (DALYs), DALY rates, and their corresponding standardized indicators. Joinpoint 5.2.0.0 software was used for time trend analysis of DALYs, age-specific DALY rates, and annual average percentage change (AAPC) values. A log-linear regression model was used to test trends for DALYs and DALY rates. Results: Compared with 1990, the prevalence and incidence of periodontal disease among Chinese women in 2021 increased by 45.67% (per 100,000 people) and 29.29% (per 100,000 people), respectively. The distribution of periodontal disease among women (15-49 years) showed a continuous and rapid upward trend, with the growth rate increasing rapidly with age. The number of cases increased the fastest in the 45-49 age group, and the prevalence increased the fastest in the 35-44 age group. The incidence of periodontal disease continued to rise with age, with the fastest increase in the 35-44 age group among women of reproductive age. The Joinpoint regression model results showed that periodontal disease led to an expanding trend in the disease burden among women of reproductive age in China, with an AAPC of DALYs = 1.20% and an AAPC of DALY rate = 1.25% (P<0.001). Conclusion The periodontal disease burden among Chinese women aged 15-49 years showed a gradually increasing trend from 1990 to 2021.

Pancreatic acinar cell carcinoma (PACC) is a rare exocrine tumor of the pancreas with distinct clinical and pathological features. In recent years, advancements in molecular biology techniques have led to a deeper understanding of the molecular mechanisms underlying PACC. Progress in imaging, endoscopic, and molecular diagnostic technologies has improved the early detection rate of PACC. The primary treatment modalities for PACC include surgical resection, chemotherapy, targeted therapy and immunotherapy; however, the therapeutic efficacy still requires further improvement. This article reviews the current research status of PACC, covering its epidemiology, pathological characteristics, molecular alterations, diagnostic methods, and treatment strategies, and discusses the controversies and future directions in PACC research.

Medical students often struggle to understand and master the relevant knowledge and skills in teaching, especially in surgical teaching. Emerging 3D printing technology can help students to understand and master surgical techniques. The problem-based learning (PBL) teaching method helps students to develop their independent thinking and teamwork skills. The combination of these methods has already achieved significant success. Therefore, this article discusses the application and combining 3D printing technology with the PBL teaching method in medical teaching, particularly in urological surgery education, and provides new ideas and references for future, more diverse, and high-tech medical education.

Rare diseases pose significant diagnostic and therapeutic challenges,carrying a high disease burden,their management critically reflects a nation's public health resilience.Currently,China faces key challenges such as scarce treatments,fragmented services,and low drug accessibility in rare disease care,which urgently require systemic solutions.Digital-intelligent technology as a key breakthrough are expected to resolve the challenges in this field.Although its application in the field of rare diseases is gradually expanding,there is a lack of systematic compilation of studies to elucidate how to precisely enhance the precision,synergy and sustainability of diagnosis and treatment.The key challenges in rare disease care concentrate in four areas:inefficiency in prenatal screening,uneven distribution of medical resources,low efficiency in social organization collaboration,and ineffective information dissemination.The"4C"strategy,based on digital-intelligent technology,can address these issues:①coordination,boost prenatal screening awareness and capacity via digital-intelligent platforms to strengthen prevention;②cooperation,deepen collaboration within specialist networks,empowering institutions to enhance diagnostic capacity;③co-creation,empower support organizations to optimize resources,efficiency;④cognition,minimize information dissipation through efficient platforms,improving patient and family quality of life.This establishes an integrated digital-intelligent rare disease model encompassing"screening-diagnosis-treatment-care".

With the advancement of the "New Medical Science" reform, the "Medicine+X" model has emerged as a key direction for the future development of medical education. Multidisciplinary integration places higher demands on both educators and students. Emerging technologies, such as intelligent tutoring systems, adaptive learning platforms, intelligent campus management systems, and ChatGPT, have made personalized learning possible. Such approaches offer notable advantages, including improving learning efficiency, enhancing motivation, eliminating the spatiotemporal constraints of clinical education, and alleviating teachers′ workloads. Nevertheless, the application of artificial intelligence in personalized medical education still faces multiple challenges, such as issues of data quality and reliability, the need for faculty development, shifts in educational paradigms, and ethical considerations. This study explored the current status of artificial intelligence in personalized medical education and offered recommendations to promote its development, including strengthening the integration of technology and education, enhancing the digital literacy of educators, establishing ethical guidelines, and fostering multi-stakeholder collaboration.

In traditional teaching, medical students have limited opportunities to interact with patients, which constrains the development of their clinical skills. Virtual standardized patients offer a potential solution to this limitation. This article analyzes the advantages of virtual standardized patients and their application in clinical teaching.

Medical students often struggle to understand and master the relevant knowledge and skills in teaching, especially in surgical teaching. Emerging 3D printing technology can help students to understand and master surgical techniques. The problem-based learning (PBL) teaching method helps students to develop their independent thinking and teamwork skills. The combination of these methods has already achieved significant success. Therefore, this article discusses the application and combining 3D printing technology with the PBL teaching method in medical teaching, particularly in urological surgery education, and provides new ideas and references for future, more diverse, and high-tech medical education.