This research plan aims to compare the clinical application effects of large language models (such as DeepSeekGPT) and specialized disease GPT (such as BAIMGPT) in the consultation and management of obstructive sleep apnea (OSA). A multicenter real-world research design is adopted, involving 1000 OSA patients or high-risk individuals. Through user cross-sectional evaluations and third-party expert reviews, the performance of the two models in aspects such as convenience, friendliness, security, accuracy of problem understanding, accuracy of answers, voice interaction, visual empowerment, and the degree of patient needs is assessed. The research focuses on the roles of the two models in OSA screening, diagnostic accuracy, and personalized prevention and treatment, and explores their potential in enhancing patient education, doctor training, and coverage of primary medical care. The research results will provide empirical evidence for the optimized application of artificial intelligence technology in OSA diagnosis and treatment, and promote the development of precision medicine and health management.

Key Words: obstructive sleep apnea; BAIMGPT; DeepSeek GPT

Health management aims to prevent diseases and improve quality of life by comprehensively monitoring, analyzing, and evaluating the health status of individuals or groups. The application of metaverse technology can further enhance the comprehensiveness, accuracy, interactivity, innovation, and personalization of health management, providing better health protection for human. However, it is also necessary to note that metaverse technology may have problems such as data privacy and technical thresholds during application, which require corresponding measures to prevent and solve.

Key Words: health management; virtual reality; augmented reality; artificial intelligence; internet of things; metaverse in medicine

This review synthesizes the innovative hardware technologies and interactive experiences of metaverse medical platforms. With the rapid development of digital technology, metaverse medical platforms are gradually becoming a reality, integrating technologies such as virtual reality (VR), augmented reality (AR), and 3D modeling, bringing revolutionary changes to the medical industry. The article first explores the value of hardware entry construction, including immersive experiences and AR technology that improves the accuracy of surgical operations. It then analyzes the objectives and implementation methods of human-computer interaction, including gesture, eye tracking, voice, and brain-computer interface interactions. The paper also discusses the application of avatars in person-to-person interaction, as well as the importance of guidance, consistency, and accuracy to user experience. Finally, it provides a prospective analysis of the future trends of metaverse medical platforms and suggests methods and standards for implementation. This article aims to provide medical professionals and researchers with a comprehensive perspective on the development of metaverse medical platforms.

Key Words: metaverse medical platform; human-computer interaction; virtual reality； augmented reality; data visualization; personalized healthcare

This paper discusses the needs and implementation of meta-hospitals from the perspectives of value, society, culture, and technology, and describes the basic architecture of meta-hospitals from the perspectives of integrating digital twins and digital natives. Based on the trend of technological development and a certain extension prediction, this paper attempts to semi-quantitatively analyze the feasibility of the infrastructure construction of the meta-hospital, and also emphasizes that the formation of the meta-hospital collaborative development system will be a long-term process. 

Key Words: meta-hospital; digital twin; digital native

Objective: To investigate the impact of precise nursing care based on dynamic nursing quality feedback model on the postoperative recovery of elderly patients undergoing radical resection for colon cancer, with a particular focus on its effects on psychological flexibility. Methods: Medical records of 124 elderly patients undergoing radical resection for colon cancer at The First Affiliated Hospital of Baotou Medical College between January 2021 and May 2024 were retrospectively analyzed in this study. Based on the received nursing interventions, the patients were divided into a control group (standard nursing care) and an observation group (precise nursing care based on a dynamic nursing quality feedback model). Results: The observation group exhibited significantly higher levels of hemoglobin, prealbumin, and albumin compared to the control group. Additionally, the observation group had lower scores in somatization, interpersonal sensitivity, depression, anxiety, obsessions-compulsions, hostility, phobic anxiety, psychoticism, and paranoid ideation. The observation group also demonstrated higher scores in active coping, self-efficacy, and the management of emotions, life, and symptoms. Improvements were also observed in nursing quality, perioperative intervention, satisfaction with rehabilitation guidance, and awareness of regular re examinations, diet intervention, and complication prevention (all with P<0.05). Conclusion: Precise nursing based on a dynamic nursing quality feedback model can improve nutritional status and medical coping style, reduce psychological issues, and enhance self-management abilities in elderly patients following radical resection of colon cancer. Additionally, it increases nursing satisfaction and raises awareness regarding the importance of regular reexaminations and complication prevention.

Biological clock genes, which regulate the body’s circadian rhythm, play a crucial role in pancreatic cancer development. The abnormal expression of these genes is closely associated with malignant proliferation, invasion, metastasis, and resistance to chemotherapy. Several biological clock genes in pancreatic cancer tissues contribute to tumor progression by modulating key signaling pathways. Moreover, disruptions in circadian clock genes are significantly linked to poor prognosis and may serve as diagnostic markers and prognostic indicators. This review summarizes recent research on the regulatory mechanisms of biological clock genes in pancreatic cancer, emphasizing their potential clinical applications as diagnostic markers, therapeutic targets, and prognostic tools. These findings may lead to new approaches for personalized pancreatic cancer treatment.

Objective: To explore the application and effectiveness of a teaching method combining a distance teaching system with case-based learning (CBL) in clinical anesthesiology experimental teaching. This study aims to provide a reference for reforming practical teaching in the anesthesiology curriculum. Methods: Sixty undergraduate students majoring in anesthesiology from the Class of 2021 at Wannan Medical College were randomly divided into two groups. The control group (30 students) received traditional classroom teaching combined with a procedural demonstration. The observation group(30 students) was taught using the distance teaching system integrated with the CBL method. Epidural anesthesia was used as the teaching topic. After the course, the teaching effect was evaluated through a theoretical examination, a clinical skills assessment, and a satisfaction questionnaire. Results: The observation group scored significantly higher than the control group in both the theoretical knowledge examination (93.93±2.99 vs. 87.80±5.52) and the clinical skills assessment (90.43±8.88 vs. 82.73±6.65) (both P<0.05). Furthermore, the student satisfaction rate in the observation group (96.67%) was significantly higher than that in the control group (83.33%) (P<0.05). Conclusion: The combination of a distance teaching system and the CBL teaching method effectively addresses the common disconnect between clinical practice and experimental learning, as well as the limited operative view in traditional teaching. By integrating live broadcasts of real clinical scenarios with case-driven learning, this approach significantly enhances students' theoretical application ability, clinical operation skills, and learning satisfaction. This model offers a promising and scalable innovation for clinical anesthesiology experimental teaching.

Combat trauma hemostasis techniques are crucial for modern military medicine in addressing the challenges posed by high-energy destructive weapons. As reported, the incidence of vascular injuries during the Vietnam War was approximately 2%, while that during the Iraq War ranged from 4.4% to 8.2%. Meanwhile, massive hemorrhage caused by various types of vascular injuries is the primary factor leading to acute death among potentially survivable casualties during wartime. This paper provides a detailed exploration of the research progress in combat trauma hemostasis, with a focus on analyzing vascular injuries and uncontrolled bleeding caused by high-energy destructive weapons in modern warfare. Starting from the pathophysiological characteristics of combat trauma, it introduces the four-level priority treatment system established by North Atlantic Treaty Organization and Committee on Tactical Combat Casualty Care, and emphasizes the importance of the “Golden 1-Hour” principle in improving casualty survival rates. The physiological mechanisms of blood coagulation are outlined, followed by an in-depth analysis of both traditional and novel hemostatic techniques, including tourniquets, hemostatic dressings, and auxiliary hemostatic materials. Finally, the challenges faced by combat trauma hemostasis technologies are discussed, along with future development directions.

This paper addresses the full-cycle medical education system that integrates "undergraduate medical education—postgraduate medical education—continuing medical education." It proposes the design and development approach of the "Huisheng Intelligent Education" metaverse platform to address current challenges, including outdated educational resources, unequal clinical practice opportunities, the tension between standardized training and personalized development, and fragmented management across different stages. The platform leverages extended reality and artificial intelligence as core technologies to construct four key components: a medical knowledge ecosystem, virtual teaching scenarios, a comprehensive teaching intelligence system, and a full-cycle teaching management hub. These components form a closed-loop path for knowledge delivery, situational training, process tracing, assessment and feedback, personalized guidance, and governance improvement. The early practice example is the metaverse-based multi-disciplinary team (MDT) teaching unit for difficult-to-diagnose pulmonary nodules, aimed at training residents in image interpretation, risk stratification, consensus formation, and doctor-patient communication. It supports synchronized participation of residents from both Shanghai and Xiamen hospitals in the same virtual space, providing consistent teaching and review, thus laying the foundation for subsequent objective evaluations and scalable implementation.

Key Words: full-cycle medical education; training and management; huisheng intelligent education; metaverse platform