This study systematically analyzed the global research landscape, technological composition, and core patents in the field of networks target and network pharmacology, and proposes further suggestions based on the IncoPat patent citation database and VOSviewer bibliometric network visualization tool. Using patent literature metrics and scientific knowledge mapping method, technological innovation pathways, research hotspots, and future directions in this field were further revealed. In particular, this field is moving towards data-driven, intelligent, and systematic approaches. Patent analysis indicated that most patent applications in this domain focused on traditional Chinese medicine(TCM), which have provided key engineering technical approaches to explore and solve complex problems of TCM. By integrating big data and artificial intelligence technologies, network targets and network pharmacology have conferred high-precision screening and quality control of key components and targets in herbal formulations and prescriptions, accelerating the clinical translation and industrialization of TCM-based new drugs and health products with medicine-food homology. Therefore, it is essential to optimize the patent protection system and establish integrated technology platforms in this field for ensuring the competitiveness of technological achievements in research and clinical application. These efforts will advance the widespread application and high-quality development of TCM modernization, precision medicine, and innovative drug discovery.
Bibliometrics ; Patents as Topic ; Humans ; Medicine, Chinese Traditional ; Network Pharmacology/trends* ; Drugs, Chinese Herbal/pharmacology*

Body weight abnormalities, including overweight, obesity, and underweight, have become a dual public health challenge in Chinese adults: overweight and obesity lead to a variety of chronic complications, while underweight increases the risks of malnutrition, sarcopenia, and organ dysfunction. To systematically address these issues, multidisciplinary experts in endocrinology, sports science, nutrition, and psychiatry from various regions have held multiple weight management seminars. Based on the latest epidemiological data and clinical evidence, they expanded the guideline to include assessment and intervention strategies for underweight, in addition to the core content of obesity management. This guideline outlines the etiological mechanisms, evaluation methods, and multidimensional management strategies for overweight and obesity, covering key areas such as diagnosis and assessment, medical nutrition therapy, exercise prescription, pharmacological intervention, and psychological support. It is intended to provide a scientific and standardized approach to weight management across the adult population, aiming to curb the rising prevalence of obesity, mitigate complications associated with abnormal body weight, and improve nutritional status and overall quality of life.

Objective:To explore the feasibility of selecting appropriate respiratory motion management strategies for patients undergoing stereotactic radiotherapy for liver cancer using chi-square feature testing and machine learning techniques.Methods:A retrospective analysis was conducted on 95 liver cancer patients who underwent respiratory motion evaluation at Xiangya Hospital of Central South University between March 2022 and August 2024. Chi-square testing was used to screen features related to respiratory motion evaluation in liver cancer patients. Based on these features, predictive models were constructed using 4 machine learning classification algorithms: support vector machine (SVM), random forest (RF), gradient boosting decision tree (GBDT), and adaptive boosting (AdaBoost). The predictive performance of these models was evaluated using accuracy, sensitivity, specificity, F1 value, and area under the curve (AUC).Results:The accuracy values for the SVM, RF, GBDT and AdaBoost models were 0.75, 0.75, 0.70, and 0.82, respectively. The sensitivity values were 0.82, 0.82, 0.64, and 0.82, respectively. The specificity values were 0.63, 0.63, 0.63, and 0.75, respectively. The F1 scores were 0.78, 0.78, 0.67, and 0.82, respectively. The AUC values were 0.85, 0.80, 0.76, and 0.85, respectively.Conclusions:The predictive models constructed by combining chi-square feature testing and machine learning methods can effectively predict the selection of respiratory motion management strategies. Among the models, the AdaBoost model demonstrated the best predictive performance for selecting respiratory motion management strategies.

The ancient Chinese people have accumulated rich experience in the process of struggling against epidemics over thou-sands of years,and established an effective theoretical system of traditional Chinese medicine(TCM)for treating epidemics,which has been applied up to now.The application of aromatic traditional Chinese medicine occupies an important position in the theoretical sys-tem of TCM for treating epidemics and the history of epidemic prevention and control.Aromatic prevention of epidemics has a profound theoretical foundation in TCM and is supported by abundant evidence from modern scientific research.It has unique advantages such as comprehensive overall regulation,participation in the whole process,action through multiple pathways,and good safety.In clinical practice,it demonstrates characteristics such as integrity,comprehensiveness,flexibility,and phase-related properties.Both its theory and prevention and treatment experience have high practical value.This article reviews the theoretical connotation,mechanism of ac-tion,and clinical application advantages of aromatic traditional Chinese medicine in preventing and treating epidemics,analyzes the challenges faced,and proposes future prospects,in order to improve the relevant theories of traditional Chinese medicine on epidemics and enhance the level of epidemic prevention and control.

The 97th Annual Meeting of the Japanese Gastric Cancer Association was held from March 12 to March 14,2025,in Nagoya,Japan.The conference was chaired by Professor Kazuhiro Uyama from Fujita Medical University and attracted nearly 2 000 scholars from around the world,including Japan,China,the republic of Korea,the United States,and Europe.With the theme of"Digital Innovation in Gastric Tumors,"the conference focused on the application of artificial intelligence,robotic surgery,and other innovations in the treatment of gastric cancer.It explored how high-precision and highly reproducible robotic surgical techniques are transforming traditional approaches to gastric cancer surgery,along with topics such as digital innovation,future medical policies,and strategies that herald a new era in healthcare.The meeting featured one main venue and 60 sub-venues with different themes,ultimately accepting 1 003 submissions.A total of 158 oral presentations covering 80 topics and 203 poster presentations were delivered.Among them,approximately 145 lectures were related to robotic surgery for gastric cancer,and when including poster presentations,nearly 255 topics were associated with gastric cancer robotic surgery.Additionally,the 7th edition of the Japanese Gastric Cancer Treatment Guidelines was released during the meeting.Our team had the honor of participating in this prestigious event.Drawing from our experience at both this conference and the 17th Annual Meeting of the Japanese Society for Robotic Surgery held in Utsunomiya,Japan,from March 7 to March 8,2025,we provide a detailed report on the latest advancements in robotic surgery for gastric cancer,hoping to offer valuable insights and references for fellow surgeons both in China and abroad.

The 97th Annual Meeting of the Japanese Gastric Cancer Association was held from March 12 to March 14,2025,in Nagoya,Japan.The conference was chaired by Professor Kazuhiro Uyama from Fujita Medical University and attracted nearly 2 000 scholars from around the world,including Japan,China,the republic of Korea,the United States,and Europe.With the theme of"Digital Innovation in Gastric Tumors,"the conference focused on the application of artificial intelligence,robotic surgery,and other innovations in the treatment of gastric cancer.It explored how high-precision and highly reproducible robotic surgical techniques are transforming traditional approaches to gastric cancer surgery,along with topics such as digital innovation,future medical policies,and strategies that herald a new era in healthcare.The meeting featured one main venue and 60 sub-venues with different themes,ultimately accepting 1 003 submissions.A total of 158 oral presentations covering 80 topics and 203 poster presentations were delivered.Among them,approximately 145 lectures were related to robotic surgery for gastric cancer,and when including poster presentations,nearly 255 topics were associated with gastric cancer robotic surgery.Additionally,the 7th edition of the Japanese Gastric Cancer Treatment Guidelines was released during the meeting.Our team had the honor of participating in this prestigious event.Drawing from our experience at both this conference and the 17th Annual Meeting of the Japanese Society for Robotic Surgery held in Utsunomiya,Japan,from March 7 to March 8,2025,we provide a detailed report on the latest advancements in robotic surgery for gastric cancer,hoping to offer valuable insights and references for fellow surgeons both in China and abroad.

The ancient Chinese people have accumulated rich experience in the process of struggling against epidemics over thou-sands of years,and established an effective theoretical system of traditional Chinese medicine(TCM)for treating epidemics,which has been applied up to now.The application of aromatic traditional Chinese medicine occupies an important position in the theoretical sys-tem of TCM for treating epidemics and the history of epidemic prevention and control.Aromatic prevention of epidemics has a profound theoretical foundation in TCM and is supported by abundant evidence from modern scientific research.It has unique advantages such as comprehensive overall regulation,participation in the whole process,action through multiple pathways,and good safety.In clinical practice,it demonstrates characteristics such as integrity,comprehensiveness,flexibility,and phase-related properties.Both its theory and prevention and treatment experience have high practical value.This article reviews the theoretical connotation,mechanism of ac-tion,and clinical application advantages of aromatic traditional Chinese medicine in preventing and treating epidemics,analyzes the challenges faced,and proposes future prospects,in order to improve the relevant theories of traditional Chinese medicine on epidemics and enhance the level of epidemic prevention and control.

Body weight abnormalities, including overweight, obesity, and underweight, have become a dual public health challenge in Chinese adults: overweight and obesity lead to a variety of chronic complications, while underweight increases the risks of malnutrition, sarcopenia, and organ dysfunction. To systematically address these issues, multidisciplinary experts in endocrinology, sports science, nutrition, and psychiatry from various regions have held multiple weight management seminars. Based on the latest epidemiological data and clinical evidence, they expanded the guideline to include assessment and intervention strategies for underweight, in addition to the core content of obesity management. This guideline outlines the etiological mechanisms, evaluation methods, and multidimensional management strategies for overweight and obesity, covering key areas such as diagnosis and assessment, medical nutrition therapy, exercise prescription, pharmacological intervention, and psychological support. It is intended to provide a scientific and standardized approach to weight management across the adult population, aiming to curb the rising prevalence of obesity, mitigate complications associated with abnormal body weight, and improve nutritional status and overall quality of life.

Objective:To explore the feasibility of selecting appropriate respiratory motion management strategies for patients undergoing stereotactic radiotherapy for liver cancer using chi-square feature testing and machine learning techniques.Methods:A retrospective analysis was conducted on 95 liver cancer patients who underwent respiratory motion evaluation at Xiangya Hospital of Central South University between March 2022 and August 2024. Chi-square testing was used to screen features related to respiratory motion evaluation in liver cancer patients. Based on these features, predictive models were constructed using 4 machine learning classification algorithms: support vector machine (SVM), random forest (RF), gradient boosting decision tree (GBDT), and adaptive boosting (AdaBoost). The predictive performance of these models was evaluated using accuracy, sensitivity, specificity, F1 value, and area under the curve (AUC).Results:The accuracy values for the SVM, RF, GBDT and AdaBoost models were 0.75, 0.75, 0.70, and 0.82, respectively. The sensitivity values were 0.82, 0.82, 0.64, and 0.82, respectively. The specificity values were 0.63, 0.63, 0.63, and 0.75, respectively. The F1 scores were 0.78, 0.78, 0.67, and 0.82, respectively. The AUC values were 0.85, 0.80, 0.76, and 0.85, respectively.Conclusions:The predictive models constructed by combining chi-square feature testing and machine learning methods can effectively predict the selection of respiratory motion management strategies. Among the models, the AdaBoost model demonstrated the best predictive performance for selecting respiratory motion management strategies.

Objective:To examine the mid - and long-term outcomes of surgical treatment of brachiocephalic Takayasu arteritis.Methods:This is a retrospective case series study. The clinical data of 39 patients,which had been diagnosed as brachiocephalic Takayasu arteritis (244 cases),who underwent surgical treatment,were analyzed between July 2012 to November 2022 at Department of Endoluminal Vascular Surgery, the First Affiliated Hospital of Zhengzhou University. There were 5 males and 34 females, aged (37.9±14.0)years (range:13 to 71 years). Despite medical treatment, the patients suffered severe ischemic symptoms continually and then underwent surgical interventions. Among them, 20 patients underwent endovascular procedures, 11 underwent open surgical procedures, and 8 underwent hybrid procedures. Patients were followed up through outpatient visits at 1, 3, 6 months after surgery and once every year later. Follow-up was conducted until November 2022. Operation status, postoperative complications and re-intervention of patients were recorded and the Kaplan-Meier survival curves were used to analyze postoperative vascular patency rates.Results:All 39 surgeries were successful, with no intraoperative death or serious complications. The follow-up period was (48.8±38.2) months(range:1 to 123 months). Thirty-three patients experienced symptom relief after surgery, and 6 patients required secondary surgical interventions. The patency rates for the endovascular treatment group at 1-, 3-, 5-, and 10-year were 95.0%, 75.2%, 60.2%, and 60.2%, respectively, while the patency rates for open surgery were all 90.9%. In the hybrid surgery group, the patency rates at 1-, 3-, 5-, and 8-year were all 87.5%.Conclusion:For patients with brachiocephalic Takayasu arteritis, choice of an appropriate blood flow revascularization intervention should be based on the patient′s condition,and the mid-and long-term outcomes are satisfactory.