Objective To analyze the current status, hotspots, and trends of global disease burden research from 2015 to 2024 based on bibliometric methods, and to provide references for public health policy-making and academic research. Methods Disease burden-related literature was retrieved from the Web of Science Core Collection database, and visual analysis was conducted using CiteSpace 6.2.R4 software, including publication volume, subject distribution, national/institutional collaboration, author co-citation networks, keyword co-occurrence, clustering, and burst analysis. Results A total of 1 852 valid articles were included. The annual publication volume showed a growing trend, and entered a rapid growth phase after 2020 (with an average annual growth rate of 17.24%). The United States, China, the United Kingdom, and Germany had the highest publication volumes, with public health, internal medicine, and epidemiology being the main subject areas. The author co-citation network indicated that Younossi ZM, Lozano R, and others were core authors, while the Chinese University of Hong Kong and Aga Khan University were at the core of the institutional collaboration network. High-frequency keywords were focused on ^“prevalence^”, ^“mortality^”, and ^“risk factors^”, and clustering analysis formed seven themes, including disease burden assessment methods (such as disability-adjusted life years), specific diseases (such as chronic obstructive pulmonary disease), and data resources (such as National Health and Nutrition Examination Survey). Burst analysis divided the research into three stages: 2015-2017 focused on infectious diseases (such as hepatitis C), 2018-2019 shifted to chronic non-communicable diseases (such as metabolic syndrome), and 2020-2024 focused on emerging fields such as viral-related diseases and cancer treatment. Conclusion Global disease burden research exhibits characteristics of multidisciplinary crossover. In the future, it is necessary to strengthen interdisciplinary collaboration, integrate big data and artificial intelligence technologies, focus on emerging health issues, and promote the transformation of research findings into policy.

ObjectiveTo establish a reliable chronic obstructive pulmonary disease (COPD) mouse model based on a self-developed multichannel automatic control system for long-term continuous cigarette smoke exposure in small animals using a novel continuous cigarette smoke exposure method, and to conduct phenotypic evaluation and analysis, thereby providing an animal experimental basis for investigating COPD pathogenesis and prevention strategies. MethodsTwenty male C57BL/6J mice aged 6 weeks were randomly and equally divided into a control group and a model group. The model group (n=10) underwent 6 h of continuous cigarette smoke exposure daily (6 cigarettes per day for 12 consecutive weeks), while the control group (n=10) received no intervention. Body weight was monitored biweekly. Post-exposure, in vivo micro-CT imaging was performed. After euthanasia, serum and bronchoalveolar lavage fluid (BALF) levels of interleukin-6 (IL-6) and tumor necrosis factor-α (TNF-α) were quantified by ELISA. Lung tissues underwent H&E and Masson's trichrome staining to observe changes in lung morphology and inflammatory cell infiltration, and the mean linear intercept (MLI) was calculated, thereby comprehensively evaluating the clinical features of COPD in the mouse model. ResultsCompared with the control group, the model group showed significantly reduced body weight (P<0.01) from the fourth week. Compared with the control group, IL-6 level in the serum and BALF of the model group increased by 27.2% and 140.0%, respectively (P<0.01). TNF-α level in the serum and bronchoalveolar lavage fluid of the model group increased by 16.7% (P<0.01) and 19.3% (P<0.05), respectively. Histopathological examination revealed alveolar wall thinning, septal rupture, emphysematous bullae formation, reduced alveolar count, bronchial wall thickening with lumen narrowing, and inflammatory cell infiltration. MLI was significantly elevated (P<0.01). Masson's staining confirmed collagen deposition and bronchial remodeling. Micro-CT demonstrated localized high-density shadows exhibiting typical features of chronic bronchitis. Conclusion The self-developed device enables long-term continuous smoke exposure, and the successfully established COPD mouse model exhibits pathological features highly consistent with clinical manifestations, offering an efficient and reliable tool for COPD research.

The Pharmacovigilance Guidelines for Clinical Application of Traditional Chinese Medicine Injections （hereinafter referred to as the Guidelines） were released by the China Association of Chinese Medicine， with the standard number T/CACM 1563.4—2024. It is the first specialized guideline in China on the approach to pharmacovigilance activities for the clinical application of traditional Chinese medicine injections （TCMIs）. The Guidelines were jointly developed by the Institute of Basic Research in Clinical Medicine， China Academy of Chinese Medical Sciences， along with 30 experts in TCM pharmacovigilance， clinical practice （TCM， as well as integrated traditional Chinese and Western medicine），and evidence-based medicine from across the country. This publication filled the gap in standard documents in this field， both domestically and internationally. The Guidelines were formulated according to GB/T1.1—2020 Directives for standardization—Part 1： Rules for the structure and drafting of standardizing documents， the WHO Handbook for Guideline Development，and other methodological norms. Based on international norms，national laws and regulations，and scientific research results in the field of pharmacovigilance， methods adopted included expert interviews，literature research，nominal group technique， and Delphi method. Then， key points for pharmacovigilance for TCM injections were summarized and clarified in the four critical sections of "monitoring"，"identification"，"assessment"，and "control". The development process of the Guidelines included project initiation， international registration， expert interviews， literature search， and evaluation. Based on the research results of these steps，a draft was formed and revised through multiple rounds of in-group expert discussion and peer evaluations by 56 external experts. After revisions by the working group based on the feedback， the final version was formed. The Guidelines came into effect on January 8，2024，providing suggestions and reference norms for pharmacovigilance in the clinical application of TCMIs. To further promote the application and popularization of the Guidelines and help pharmacovigilance personnel better understand the development process，this study elucidates the background，methodological framework，and key development steps of the Guidelines.

The Pharmacovigilance Guideline for Clinical Application of Chinese Patent Medicine for External Use （T/CACM 1563.5—2024）， the first guideline in China specializing for the clinical safety of Chinese patent medicines for external use， was led by the Institute of Basic Research in Clinical Medicine，China Academy of Chinese Medical Sciences，and jointly developed by more than 30 research institutions of medical sciences across the country. Aiming to standardize the pharmacovigilance activities in the clinical application of Chinese patent medicines for external use，the guideline systematically categorizes potential risks and proposes prevention and control measures that cover 11 core sections of risk monitoring and reporting， signal identification，as well as assessment and control， addressing the gap in domestic and international standardization of this field. The compilation of this guideline strictly adhered to international norms and domestic regulations， involving multiple rounds of expert consultations，hybrid interviews， and evidence integration （covering literature，medical insurance，essential medicine，pharmacopoeia data， and regulatory information）. With the scope of application defined to include medical institutions， pharmaceutical manufacturers and distribution enterprises，as well as regulatory authorities， the guideline focuses on key issues such as inherent medicine risks，quality risks，off-label use，risks of combination therapy，and the safety in special populations. During the compilation，core discrepancies such as the definition of application scope and quality risk control were addressed to ensure alignment with regulations such as the Drug Administration Law of the People's Republic of China and the Good Pharmacovigilance Practice. The guideline is registered internationally （PREPARE—2022CN463）. In the future，the implementation of the guideline will be promoted through hierarchical dissemination，dynamic revision，and post-effectiveness evaluation， contributing to rational clinical use and improved patient safety.

The Pharmacovigilance Guidelines for Clinical Application of Traditional Chinese Medicine Injections （hereinafter referred to as the Guidelines） were released by the China Association of Chinese Medicine， with the standard number T/CACM 1563.4—2024. It is the first specialized guideline in China on the approach to pharmacovigilance activities for the clinical application of traditional Chinese medicine injections （TCMIs）. The Guidelines were jointly developed by the Institute of Basic Research in Clinical Medicine， China Academy of Chinese Medical Sciences， along with 30 experts in TCM pharmacovigilance， clinical practice （TCM， as well as integrated traditional Chinese and Western medicine），and evidence-based medicine from across the country. This publication filled the gap in standard documents in this field， both domestically and internationally. The Guidelines were formulated according to GB/T1.1—2020 Directives for standardization—Part 1： Rules for the structure and drafting of standardizing documents， the WHO Handbook for Guideline Development，and other methodological norms. Based on international norms，national laws and regulations，and scientific research results in the field of pharmacovigilance， methods adopted included expert interviews，literature research，nominal group technique， and Delphi method. Then， key points for pharmacovigilance for TCM injections were summarized and clarified in the four critical sections of "monitoring"，"identification"，"assessment"，and "control". The development process of the Guidelines included project initiation， international registration， expert interviews， literature search， and evaluation. Based on the research results of these steps，a draft was formed and revised through multiple rounds of in-group expert discussion and peer evaluations by 56 external experts. After revisions by the working group based on the feedback， the final version was formed. The Guidelines came into effect on January 8，2024，providing suggestions and reference norms for pharmacovigilance in the clinical application of TCMIs. To further promote the application and popularization of the Guidelines and help pharmacovigilance personnel better understand the development process，this study elucidates the background，methodological framework，and key development steps of the Guidelines.

The Pharmacovigilance Guideline for Clinical Application of Chinese Patent Medicine for External Use （T/CACM 1563.5—2024）， the first guideline in China specializing for the clinical safety of Chinese patent medicines for external use， was led by the Institute of Basic Research in Clinical Medicine，China Academy of Chinese Medical Sciences，and jointly developed by more than 30 research institutions of medical sciences across the country. Aiming to standardize the pharmacovigilance activities in the clinical application of Chinese patent medicines for external use，the guideline systematically categorizes potential risks and proposes prevention and control measures that cover 11 core sections of risk monitoring and reporting， signal identification，as well as assessment and control， addressing the gap in domestic and international standardization of this field. The compilation of this guideline strictly adhered to international norms and domestic regulations， involving multiple rounds of expert consultations，hybrid interviews， and evidence integration （covering literature，medical insurance，essential medicine，pharmacopoeia data， and regulatory information）. With the scope of application defined to include medical institutions， pharmaceutical manufacturers and distribution enterprises，as well as regulatory authorities， the guideline focuses on key issues such as inherent medicine risks，quality risks，off-label use，risks of combination therapy，and the safety in special populations. During the compilation，core discrepancies such as the definition of application scope and quality risk control were addressed to ensure alignment with regulations such as the Drug Administration Law of the People's Republic of China and the Good Pharmacovigilance Practice. The guideline is registered internationally （PREPARE—2022CN463）. In the future，the implementation of the guideline will be promoted through hierarchical dissemination，dynamic revision，and post-effectiveness evaluation， contributing to rational clinical use and improved patient safety.

It is very limited that the benefit of perioperative chemotherapy in early non-small cell lung cancer (NSCLC), and the 5-year survival rate is only 5% higher than surgery. Antibodies that block programmed cell death protein 1/programmed death-ligand 1 significantly improve the survival of advanced NSCLC. The value of immunotherapy in early NSCLC is also being explored. This paper firstly summarized and analyzed the progress of immunotherapy in the perioperative period of NSCLC. Secondly, the safety and feasibility of surgical resection after neoadjuvant immunotherapy were discussed. Finally, the clinical value of different therapeutic efficacy prediction indicators was summarized, in order to clarify the current status of immunotherapy in the perioperative period, so as to improve the clinical benefits of early NSCLC patients.

Osteoarthritis （OA） and stroke are common clinical diseases that reduce patients' quality of life and place a burden on families and society. Ruyi Zhenbaowan， a classic prescription in Tibetan medicine， have the functions of clearing heat， awakening the brain and opening orifices， relaxing tendons and promoting meridian circulation， and eliminating yellow water. Clinically， they are used to treat osteoarthritis， post-stroke sequelae， neuropathic pain， and other related conditions. Modern pharmacological studies have demonstrated their anti-inflammatory， analgesic， and nerve-repairing effects. However， current research remains insufficient regarding the appropriate indications， timing， and efficacy of this medicine in treating relevant diseases. To enhance clinicians' understanding of this medicine and promote its standardized and rational clinical use， a panel of national experts， including clinical specialists， Tibetan medicine practitioners， pharmacologists， and methodologists， formulated this consensus based on clinical experience and evidence-based practice. The Cochrane systematic review framework， the Grading of Recommendations Assessment， Development and Evaluation （GRADE） system， and the nominal group method were employed to generate seven graded recommendations and 19 consensus-based suggestions. These recommendations clearly define the key points in the clinical application of Ruyi Zhenbaowan， including therapeutic indications， dosage and administration， treatment duration， and medication safety. The consensus specifically addresses the clinical efficacy， appropriate timing of administration， dosage strategies， treatment cycles， and combination medication strategies for treating osteoarthritis and stroke and provides an overview of safety considerations. The aim is to provide standardized guidance for hospitals and healthcare institutions nationwide to ensure the rational application of Ruyi Zhenbaowan in the treatment of osteoarthritis and stroke， reduce medication-related risks， and further leverage its clinical advantages. This consensus has been approved and issued by the China Association of Chinese Medicine， with the standard number GS/CACM 369-2024.

Patients with periodontal disease often require combined periodontal-orthodontic interventions to restore periodontal health, function, and aesthetics, ensuring both patient satisfaction and long-term stability. Managing these patients involving orthodontic tooth movement can be particularly challenging due to compromised periodontal soft and hard tissues, especially in severe cases. Therefore, close collaboration between orthodontists and periodontists for comprehensive diagnosis and sequential treatment, along with diligent patient compliance throughout the entire process, is crucial for achieving favorable treatment outcomes. Moreover, long-term orthodontic retention and periodontal follow-up are essential to sustain treatment success. This expert consensus, informed by the latest clinical research and practical experience, addresses clinical considerations for orthodontic treatment of periodontal patients, delineating indications, objectives, procedures, and principles with the aim of providing clear and practical guidance for clinical practitioners.
Humans ; Consensus ; Orthodontics, Corrective/standards* ; Periodontal Diseases/complications* ; Tooth Movement Techniques/methods* ; Practice Guidelines as Topic

Drug-drug interaction (DDI) refers to the interaction between two or more drugs in the body, altering their efficacy or pharmacokinetics. Fully considering and accurately predicting DDI has become an indispensable part of ensuring safe medication for patients. In recent years, many deep learning-based methods have been proposed to predict DDI. However, most existing computational models tend to oversimplify the fusion of drug structural and topological information, often relying on methods such as splicing or weighted summation, which fail to adequately capture the potential complementarity between structural and topological features. This loss of information may lead to models that do not fully leverage these features, thus limiting their performance in DDI prediction. To address these challenges, we propose a relation-aware cross adversarial network for predicting DDI, named RCAN-DDI, which combines a relationship-aware structure feature learning module and a topological feature learning module based on DDI networks to capture multimodal features of drugs. To explore the correlations and complementarities among different information sources, the cross-adversarial network is introduced to fully integrate features from various modalities, enhancing the predictive performance of the model. The experimental results demonstrate that the RCAN-DDI method outperforms other methods. Even in cases of labelled DDI scarcity, the method exhibits good robustness in the DDI prediction task. Furthermore, the effectiveness of the cross-adversarial module is validated through ablation experiments, demonstrating its superiority in learning multimodal complementary information.