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

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.

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*

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.

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: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.

Patients with severe trauma require an extremely timely treatment and transfusion plays an irreplaceable role in the emergency treatment of such patients. An increasing number of evidence-based medicinal evidences and clinical practices suggest that patients with severe traumatic bleeding benefit from early transfusion of low-titer group O whole blood or hemostatic resuscitation with red blood cells, plasma and platelet of a balanced ratio. However, the current domestic mode of blood supply cannot fully meet the requirements of timely and effective blood transfusion for emergency treatment of patients with severe trauma in clinical practice. In order to solve the key problems in blood supply and blood transfusion strategies for emergency treatment of severe trauma, Branch of Clinical Transfusion Medicine of Chinese Medical Association, Group for Trauma Emergency Care and Multiple Injuries of Trauma Branch of Chinese Medical Association, Young Scholar Group of Disaster Medicine Branch of Chinese Medical Association organized domestic experts of blood transfusion medicine and trauma treatment to jointly formulate Chinese expert consensus on blood support mode and blood transfusion strategies for emergency treatment of severe trauma patients ( version 2024). Based on the evidence-based medical evidence and Delphi method of expert consultation and voting, 10 recommendations were put forward from two aspects of blood support mode and transfusion strategies, aiming to provide a reference for transfusion resuscitation in the emergency treatment of severe trauma and further improve the success rate of treatment of patients with severe trauma.