Based on traditional Chinese medicine （TCM） theory and modern scientific research， and in accordance with the core functions of the Belt Channel in girdling and regulation of qi movement， a preliminary framework of the Belt Channel network hypothesis is constructed. It is proposed that the Belt Channel network consists of three synergistic subsystems， fascial biomechanics， neural conduction， and endocrine metabolism. Structurally， it is based on a "biomechanical ring" formed by the transversalis fascia and the core muscle group. Functionally， it integrates signals through the lumbosacral plexus and the autonomic nervous system， and is capable of regulating the hypothalamic-pituitary-target gland axis and immune homeostasis. Compared with other longitudinal meridians， the uniqueness of the Belt Channel network lies in its dual regulatory effects in coordinating somatic and visceral girdling and in maintaining systemic homeostasis. By integrating the traditional theory of the Belt Channel with mechanisms identified in modern research， this study provides new insights into the modern interpretation of the Belt Channel functions in girdling and regulation of qi movement， as well as the expansion of its clinical applications.

The expert consensus on the clinical treatment of herpes zoster with fire needling was developed, and the commonly used fire needling treatment scheme verified by clinical research was selected to form a standardized diagnosis and treatment scheme for acute herpes zoster and postherpetic neuralgia (PHN), so as to answer the core problems in clinical application. The consensus focuses on patients with herpes zoster, and forms recommendations for 9 key clinical issues, covering simple fire needling and TCM comprehensive therapy based on fire needling, including fire needling combined with cupping, fire needling combined with Chinese herb, fire needling combined with cupping and Chinese herb, fire needling combined with filiform needling, fire needling combined with moxibustion, and provides specific recommendations and operational guidelines for various therapies.
Humans ; Herpes Zoster/therapy* ; Acupuncture Therapy/instrumentation* ; Consensus ; Clinical Protocols

Objective:Interpret the key differences between the China Health-care Security Diagnosis Related Groups(CHS-DRG)2.0 and CHS-DRG 1.1,and provide reference for optimizing management strategies in medical institutions.Methods:Text analysis was used to import the CHS-DRG 2.0 and 1.1 grouping scheme dictionary data into the SQL database in a structured table format using SQL Server 2014.The key differences between the two schemes in grouping structure,grouping rules,grouping results,and other aspects were identified.Results:CHS-DRG 2.0 version added 26 groups,deleted 3 groups,and refined 10 groups into 20 groups for 14 clinical specialties at the ADRG level compared to CHS-DRG 1.1.Some group codes,names,and grouping rules were adjusted;Adjusted some grouping conditions and grouping results at the DRG level.Conclusion:CHS-DRG 2.0 version has improved grouping efficiency compared to CHS-DRG 1.1,solved some clinical bottleneck problems,and standardized the role of clinical diagnosis in grouping from the perspective of resource consumption.However,it has not completely solved the grouping problems of multi disease co treatment,multi disease treatment,and combined surgery.The adjustment of DRG weights and rates,the follow-up of related supporting policy reforms,and the negative effects of DRG will still pose challenges for medical institutions.

With the in-depth implementation of the national strategy of"Healthy China 2030",people's understanding and de-mand for health have been constantly evolving,promoting the transformation of the health model from"disease-centered"to"people-centered".This paper discusses the characteristics and limitations of the"disease-centered"health model,proposes the connotation of the"people-centered"health model and the method of maintaining health in traditional Chinese medicine,emphasizes overall health with prevention as the main focus and individual as the center,and specifically discusses the implementation measures of the"people-centered"health model:emphasize the transformation of ideas and concepts,give full play to the advantages of modern traditional Chi-nese medicine,and establish a system network of health models.It is also related to the transformation of the active health paradigm,in order to break through the limitations of the existing health model and achieve the goal of health for all.

Objective:Interpret the key differences between the China Health-care Security Diagnosis Related Groups(CHS-DRG)2.0 and CHS-DRG 1.1,and provide reference for optimizing management strategies in medical institutions.Methods:Text analysis was used to import the CHS-DRG 2.0 and 1.1 grouping scheme dictionary data into the SQL database in a structured table format using SQL Server 2014.The key differences between the two schemes in grouping structure,grouping rules,grouping results,and other aspects were identified.Results:CHS-DRG 2.0 version added 26 groups,deleted 3 groups,and refined 10 groups into 20 groups for 14 clinical specialties at the ADRG level compared to CHS-DRG 1.1.Some group codes,names,and grouping rules were adjusted;Adjusted some grouping conditions and grouping results at the DRG level.Conclusion:CHS-DRG 2.0 version has improved grouping efficiency compared to CHS-DRG 1.1,solved some clinical bottleneck problems,and standardized the role of clinical diagnosis in grouping from the perspective of resource consumption.However,it has not completely solved the grouping problems of multi disease co treatment,multi disease treatment,and combined surgery.The adjustment of DRG weights and rates,the follow-up of related supporting policy reforms,and the negative effects of DRG will still pose challenges for medical institutions.

Computational modeling is an invaluable tool for mechanism analysis, directed engineering, and rational design of biological parts, metabolic networks, and even cellular systems. It can provide new technological solutions to address biological challenges at different levels and has become a central focus of research in biomanufacturing. In the computational modeling of proteins, which are the key parts in biological systems, the traditional physics-based methods (computer software and mathematical model) have been widely used to study the physical and chemical processes in the functioning of proteins, and have thus been recognized as a powerful tool for understanding complex biological systems and guiding experimental designs. As the scale of computational modeling continues to expand, traditional modeling techniques face difficulties in balancing computational accuracy and speed. In recent years, the explosive growth of biological data has made it possible to construct high-performance artificial intelligence (AI) models, which brings new opportunities to the computational modeling of proteins, and the AI-enhanced physics-based computational modeling technologies have emerged. This combined strategy not only incorporates the chemical knowledge and established physical principles but also is powerful in data processing and pattern recognition, which greatly improves the computational efficiency and prediction accuracy, as well as possesses stronger interpretation ability, transferability, and robustness. The AI-enhanced physics-based computational modeling technologies have already shown great potential and value in biocatalysis, paving a new way for the future development of biomanufacturing.
Artificial Intelligence ; Proteins/chemistry* ; Computer Simulation ; Software ; Computational Biology/methods*

Traditional Chinese medicine (TCM) represents a paradigmatic approach to personalized medicine, developed through the systematic accumulation and refinement of clinical empirical data over more than 2000 years, and now encompasses large-scale electronic medical records (EMR) and experimental molecular data. Artificial intelligence (AI) has demonstrated its utility in medicine through the development of various expert systems (e.g., MYCIN) since the 1970s. With the emergence of deep learning and large language models (LLMs), AI's potential in medicine shows considerable promise. Consequently, the integration of AI and TCM from both clinical and scientific perspectives presents a fundamental and promising research direction. This survey provides an insightful overview of TCM AI research, summarizing related research tasks from three perspectives: systems-level biological mechanism elucidation, real-world clinical evidence inference, and personalized clinical decision support. The review highlights representative AI methodologies alongside their applications in both TCM scientific inquiry and clinical practice. To critically assess the current state of the field, this work identifies major challenges and opportunities that constrain the development of robust research capabilities-particularly in the mechanistic understanding of TCM syndromes and herbal formulations, novel drug discovery, and the delivery of high-quality, patient-centered clinical care. The findings underscore that future advancements in AI-driven TCM research will rely on the development of high-quality, large-scale data repositories; the construction of comprehensive and domain-specific knowledge graphs (KGs); deeper insights into the biological mechanisms underpinning clinical efficacy; rigorous causal inference frameworks; and intelligent, personalized decision support systems.
Medicine, Chinese Traditional/methods* ; Artificial Intelligence ; Humans ; Precision Medicine ; Decision Support Systems, Clinical

Objective:To investigate the clinical characteristics of patients with hepatitis B virus（HBV）-related primary hepatocellular carcinoma（HCC）who were treated in a multidisciplinary team（MDT）for liver cancer，so as to provide a basis for clinical optimization of the diagnosis and treatment of patients with chronic hepatitis B（CHB）.Methods:A retrospective analysis was performed for 482 HBV-related HCC patients who were treated with HCC-MDT every Thursday afternoon in The First Affiliated Hospital of the Army Medical University from January 2022 to May 2024，aged 18-87（55.54±10.84）years，86.93%（419/482）males and 13.07%（63/482）females. According to the different underlying liver diseases at the time of initial medical treatment and the different prognostic outcomes at the later follow-up，the differences in clinical characteristics between groups under different conditions were compared and analyzed，and the influencing factors of HCC prognosis were understood by Logistic regression analysis. Results:At the time of MDT presentation，the differences in HBeAg status（ χ2=6.311 ，P=0.043），γ-glutamyl traspeptidase（GGT）（ Z=6.277， P=0.043），alkaline phosphatase（ALP）（ Z=7.236 ，P=0.027），and model for end-stage liver disease（MELD）scores（ Z=6.111， P=0.047）among patients with different underlying liver diseases were statistically significant. At follow-up，6.75%（11/163）of HBV-related HCC patients who presented to MDT had a family history of HCC，and their cumulative mortality rate was as high as 60.8%（205/337）at least for 1 year. Mulitivariate Logistic regression analysis showed that different underlying liver disease at the time of initial medical treatment，HBV DNA replication level，MELD score and choice of anti-cancer treatment regimen were the influencing factors for the prognosis of HCC（all P<0.05）. The worse the degree of cirrhosis at the initial presentation，the higher the level of HBV DNA replication，and the higher the MELD score，the worse the prognosis for HCC. Conclusion:Advancing the diagnosis and treatment of CHB，maximizing the inhibition of HBV DNA replication，reducing the MELD score，and optimizing the anti-cancer treatment regimen can reduce the mortality rate of HBV-related HCC.

With the in-depth implementation of the national strategy of"Healthy China 2030",people's understanding and de-mand for health have been constantly evolving,promoting the transformation of the health model from"disease-centered"to"people-centered".This paper discusses the characteristics and limitations of the"disease-centered"health model,proposes the connotation of the"people-centered"health model and the method of maintaining health in traditional Chinese medicine,emphasizes overall health with prevention as the main focus and individual as the center,and specifically discusses the implementation measures of the"people-centered"health model:emphasize the transformation of ideas and concepts,give full play to the advantages of modern traditional Chi-nese medicine,and establish a system network of health models.It is also related to the transformation of the active health paradigm,in order to break through the limitations of the existing health model and achieve the goal of health for all.

Objective:To investigate the clinical characteristics of patients with hepatitis B virus（HBV）-related primary hepatocellular carcinoma（HCC）who were treated in a multidisciplinary team（MDT）for liver cancer，so as to provide a basis for clinical optimization of the diagnosis and treatment of patients with chronic hepatitis B（CHB）.Methods:A retrospective analysis was performed for 482 HBV-related HCC patients who were treated with HCC-MDT every Thursday afternoon in The First Affiliated Hospital of the Army Medical University from January 2022 to May 2024，aged 18-87（55.54±10.84）years，86.93%（419/482）males and 13.07%（63/482）females. According to the different underlying liver diseases at the time of initial medical treatment and the different prognostic outcomes at the later follow-up，the differences in clinical characteristics between groups under different conditions were compared and analyzed，and the influencing factors of HCC prognosis were understood by Logistic regression analysis. Results:At the time of MDT presentation，the differences in HBeAg status（ χ2=6.311 ，P=0.043），γ-glutamyl traspeptidase（GGT）（ Z=6.277， P=0.043），alkaline phosphatase（ALP）（ Z=7.236 ，P=0.027），and model for end-stage liver disease（MELD）scores（ Z=6.111， P=0.047）among patients with different underlying liver diseases were statistically significant. At follow-up，6.75%（11/163）of HBV-related HCC patients who presented to MDT had a family history of HCC，and their cumulative mortality rate was as high as 60.8%（205/337）at least for 1 year. Mulitivariate Logistic regression analysis showed that different underlying liver disease at the time of initial medical treatment，HBV DNA replication level，MELD score and choice of anti-cancer treatment regimen were the influencing factors for the prognosis of HCC（all P<0.05）. The worse the degree of cirrhosis at the initial presentation，the higher the level of HBV DNA replication，and the higher the MELD score，the worse the prognosis for HCC. Conclusion:Advancing the diagnosis and treatment of CHB，maximizing the inhibition of HBV DNA replication，reducing the MELD score，and optimizing the anti-cancer treatment regimen can reduce the mortality rate of HBV-related HCC.