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*

Objective:To construct a prediction model for postoperative poor in-hospital prognosis in patients with traumatic brain injury (TBI) and evaluate its predictive performance.Methods:A retrospective case control study was conducted to analyze the clinical data of 1 120 TBI patients admitted to Changde Hospital Affiliated to Xiangya Medical College of Central South University from May 2019 to December 2024. The patients were divided into the training set ( n=784) and verification set ( n=336) at a ratio of 7∶3. Based on the Glasgow outcome scale-extended (GOS-E) at discharge, the training set was stratified into favorable prognosis group ( n=335, GOS-E 5-8 points) and poor prognosis group ( n=449, GOS-E 1-4 points). The two groups in the training set were compared in terms of general baseline indicators, TBI-related clinical indicators, and admission laboratory blood test results. Univariate analysis and Lasso regression analysis were employed to screen risk factors associated with postoperative poor in-hospital prognosis in TBI patients. Multivariate Logistic regression analysis was used to determine independent risk factors and construct a regression equation. The regression equation was presented using R language to create a visual nomogram for predicting postoperative poor in-hospital prognosis in TBI patients. In both the training set and verification set, the predictive performance of the model was evaluated by calculating the area under the receiver operating characteristic (ROC) curve (AUC), plotting calibration curves, and performing decision curve analysis (DCA). Results:The results of the univariate analysis indicated that the age, Charlson complication index (CCI), time from trauma to admission, time from trauma to operation, cause of injury, abbreviated injury scale (AIS) (head and neck), injury severity score (ISS), admission Glasgow coma scale (GCS), admission pupil responsiveness, multiple craniocerebral injuries, subdural hematoma, intracerebral hematoma, intraventricular hemorrhage, subarachnoid hemorrhage, decompressive craniotomy, intraoperative blood loss, intraoperative blood transfusion, traumatic cerebral infarction, postoperative delayed bleeding, epilepsy seizures, as well as the following admission tested results including red blood cell count, white blood cell count, platelet count, neutrophil percentage, percentage of lymphocytes, albumin, total bilirubin, urea nitrogen, thrombin time (TT), prothrombin time (PT), international standardized ratio (INR), glutamic aminotransferase, alanine aminotransferase, creatinine, and blood glucose were statistically different between the two groups in the training set ( P<0.05). Lasso regression analysis suggested 14 risk factors of age, CCI, cause of injury, head and neck AIS, ISS, admission GCS, admission pupil responsiveness, multiple craniocerebral injuries, subdural hematoma, intracerebral hematoma, intraoperative blood loss, admission platelet count, admission albumin, admission blood glucose for postoperative poor in-hospital prognosis. The results of the multivariate Logistic regression analysis showed that age ( OR=1.02, 95% CI 1.00, 1.03, P<0.01), CCI ( OR=1.46, 95% CI 1.02, 2.09, P<0.05), head and neck AIS ( OR=1.43, 95% CI 1.11, 1.85, P<0.01), ISS ( OR=2.16, 95% CI 1.39, 3.35, P<0.01), admission GCS ( OR=1.59, 95% CI 1.19, 2.13, P<0.01), intracerebral hematoma ( OR=4.41, 95% CI 2.15, 9.44, P<0.01), intraoperative blood loss ( OR=1.05, 95% CI 1.00, 1.09, P<0.05), admission platelet count ( OR=0.98, 95% CI 0.97, 0.99, P<0.01), admission blood glucose ( OR=1.08, 95% CI 1.02, 1.15, P<0.05) could be the main risk factors to construct a prediction model for postoperative poor in-hospital prognosis in TBI patients. Meanwhile, a regression equation was constructed: Logit[ P/(1- P)]=-2.4+ 0.02×"age"+0.38×"CCI"+0.36×"head and neck AIS"+0.77×"ISS"+0.47×"admission GCS"+1.48×"intracerebral hematoma"+0.05×intraoperative blood loss-0.02×admission platelet count+0.08×admission blood glucose. In the training set, the predictive model for poor postoperative in-hospital prognosis in TBI patients achieved an AUC of 0.87 (95% CI 0.84, 0.89), with a Youden′s index of 0.57, sensitivity of 73.70%, and specificity of 83.00%. In the verification set, the model showed an AUC of 0.80 (95% CI 0.76, 0.85), with a Youden′s index of 0.63, sensitivity of 65.20%, and specificity of 77.90%. In the training set, the Brier score for the calibration curve was 0.14 (95% CI 0.13, 0.16). In the verification set, the Brier score for the calibration curve was 0.18 (95% CI 0.15, 0.20). The DCA diagram indicated that the nomogram prediction model provided high clinical net benefit for predicting postoperative poor in-hospital prognosis in TBI patients. Conclusion:The prediction model for postoperative poor in-hospital prognosis in TBI patients, constructed based on age, CCI, head and neck AIS, ISS, admission GCS, intracerebral hematoma, intraoperative blood loss, admission platelet count, and admission blood glucose, exhibits good predictive performance.

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.

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 investigate the mechanism of action of the nuclear factor erythroid 2-related factor 2(Nrf2)/solute carrier family 7 member 11(SLC7A11)/glutathione peroxidase 4(GPX4)signaling pathway in non-alcoholic fatty liver disease(NAFLD),and to explore the mechanism of Gegen QinLian Decoction for the treatment of NAFLD,using in vivo and in vitro experiments.Methods Rats were fed with high-fat chow for 24 weeks to induce NAFLD,and were then divided randomly into normal(C),model(M),high-,medium-,and low-dose Gegen QinLian Decoction(GGQLT-H,GGQLT-M,GGQLT-L),and metformin(Met)groups.From week 25 onwards,the rats were administered the corresponding drugs by gavage for 2 weeks according to the grouping,until sampling.Levels of the oxidative stress markers malondialdehyde(MDA)and glutathione(GSH)in the liver tissues were measured in each group using biochemical kits and ferrous iron(Fe2+)in rat liver tissues was detected using a Fe2+kit.Nrf2,heme oxygenase-1(HO-1),SLC7A11,glutathione synthetase(GSS),GPX4,and acyl coenzyme A synthetase 4(ACSL4)mRNA levels in rat liver tissues were measured by reverse transcription quantitative polymerase chain reaction.For cellular experiments lipid acc umulation was induced in HepG2 hepatocellular carcinoma cells using 1 mmol/L free fatty acid,to mimic the NAFLD in vitro model.Different concentrations of Gegen QinLian Decoction and metformin-containing serum were added for treatment.Lipid accumulation was detected in the cells in each group by Oil red O staining.The MDA and GSH contents of HepG2 cells in the different groups were determined using appropriate kits,and the ferrous contents were detected using a cell-specific ferrous kit.Expression levels of Nrf2,HO-1,SLC7A11,GSS,GPX4,and ACSL4 mRNA was detected in each group of cells using reverse transcription quantitative polymerase chain reaction.Results In the animal experiments,MDA and Fe2+liver levels were significantly higher in the M group than in the C group,while GSH levels were significantly lower(P＜0.01).GGQLT-H,GGQLT-M and Met groups showed significantly reduced MDA and Fe2+and elevated GSH levels compared with the M group(P＜0.01,P＜0.05).High-and medium-dose Gegen QinLian Decoction and metformin increased Nrf2,HO-1,GSS,and GPX4 mRNA and decreased ACSL4 mRNA expression levels(P＜0.01,P＜0.05).In cellular experiments,lipid droplets were significantly increased in the HepG2 cell M group compared with those in the C group,and lipid droplets were significantly reduced by Gegen QinLian Decoction and metformin.MDA and Fe2+levels were significantly increased and GSH levels were significantly decreased in the HepG2 M group compared with the levels in the C group(P＜0.01),while all doses of Gegen QinLian Decoction and metformin significantly decreased MDA and Fe2+levels(P＜0.01)and increased the GSH content(P＜0.01,P＜0.05).Nrf2,GSS,GPX4,and SLC7A11 mRNA expression levels in the GGQLT-H group,Nrf2,HO-1,and SLC7A11 in the GGQLT-L group,HO-1,SLC7A11,and GSS in the GGQLT-M group,and GSS,Nrf2,and HO-1 in the Met group were all significantly increased compared with the findings in the M group(P＜0.01,P＜0.05).ACSL4 mRNA expression levels were significantly decreased in the GGQLT-M and GGQLT-L groups and the Met group(P＜0.01,P＜0.05).Conclusions Gegen QinLian Decoction can improve NAFLD by inhibiting ferroptosis,and its mechanism may he related to regulation of the Nrf2/SLC7A 11/GPX4 signaling pathway.

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.

Objective To investigate the mechanism of action of the nuclear factor erythroid 2-related factor 2(Nrf2)/solute carrier family 7 member 11(SLC7A11)/glutathione peroxidase 4(GPX4)signaling pathway in non-alcoholic fatty liver disease(NAFLD),and to explore the mechanism of Gegen QinLian Decoction for the treatment of NAFLD,using in vivo and in vitro experiments.Methods Rats were fed with high-fat chow for 24 weeks to induce NAFLD,and were then divided randomly into normal(C),model(M),high-,medium-,and low-dose Gegen QinLian Decoction(GGQLT-H,GGQLT-M,GGQLT-L),and metformin(Met)groups.From week 25 onwards,the rats were administered the corresponding drugs by gavage for 2 weeks according to the grouping,until sampling.Levels of the oxidative stress markers malondialdehyde(MDA)and glutathione(GSH)in the liver tissues were measured in each group using biochemical kits and ferrous iron(Fe2+)in rat liver tissues was detected using a Fe2+kit.Nrf2,heme oxygenase-1(HO-1),SLC7A11,glutathione synthetase(GSS),GPX4,and acyl coenzyme A synthetase 4(ACSL4)mRNA levels in rat liver tissues were measured by reverse transcription quantitative polymerase chain reaction.For cellular experiments lipid acc umulation was induced in HepG2 hepatocellular carcinoma cells using 1 mmol/L free fatty acid,to mimic the NAFLD in vitro model.Different concentrations of Gegen QinLian Decoction and metformin-containing serum were added for treatment.Lipid accumulation was detected in the cells in each group by Oil red O staining.The MDA and GSH contents of HepG2 cells in the different groups were determined using appropriate kits,and the ferrous contents were detected using a cell-specific ferrous kit.Expression levels of Nrf2,HO-1,SLC7A11,GSS,GPX4,and ACSL4 mRNA was detected in each group of cells using reverse transcription quantitative polymerase chain reaction.Results In the animal experiments,MDA and Fe2+liver levels were significantly higher in the M group than in the C group,while GSH levels were significantly lower(P＜0.01).GGQLT-H,GGQLT-M and Met groups showed significantly reduced MDA and Fe2+and elevated GSH levels compared with the M group(P＜0.01,P＜0.05).High-and medium-dose Gegen QinLian Decoction and metformin increased Nrf2,HO-1,GSS,and GPX4 mRNA and decreased ACSL4 mRNA expression levels(P＜0.01,P＜0.05).In cellular experiments,lipid droplets were significantly increased in the HepG2 cell M group compared with those in the C group,and lipid droplets were significantly reduced by Gegen QinLian Decoction and metformin.MDA and Fe2+levels were significantly increased and GSH levels were significantly decreased in the HepG2 M group compared with the levels in the C group(P＜0.01),while all doses of Gegen QinLian Decoction and metformin significantly decreased MDA and Fe2+levels(P＜0.01)and increased the GSH content(P＜0.01,P＜0.05).Nrf2,GSS,GPX4,and SLC7A11 mRNA expression levels in the GGQLT-H group,Nrf2,HO-1,and SLC7A11 in the GGQLT-L group,HO-1,SLC7A11,and GSS in the GGQLT-M group,and GSS,Nrf2,and HO-1 in the Met group were all significantly increased compared with the findings in the M group(P＜0.01,P＜0.05).ACSL4 mRNA expression levels were significantly decreased in the GGQLT-M and GGQLT-L groups and the Met group(P＜0.01,P＜0.05).Conclusions Gegen QinLian Decoction can improve NAFLD by inhibiting ferroptosis,and its mechanism may he related to regulation of the Nrf2/SLC7A 11/GPX4 signaling pathway.

Objective:To construct a prediction model for postoperative poor in-hospital prognosis in patients with traumatic brain injury (TBI) and evaluate its predictive performance.Methods:A retrospective case control study was conducted to analyze the clinical data of 1 120 TBI patients admitted to Changde Hospital Affiliated to Xiangya Medical College of Central South University from May 2019 to December 2024. The patients were divided into the training set ( n=784) and verification set ( n=336) at a ratio of 7∶3. Based on the Glasgow outcome scale-extended (GOS-E) at discharge, the training set was stratified into favorable prognosis group ( n=335, GOS-E 5-8 points) and poor prognosis group ( n=449, GOS-E 1-4 points). The two groups in the training set were compared in terms of general baseline indicators, TBI-related clinical indicators, and admission laboratory blood test results. Univariate analysis and Lasso regression analysis were employed to screen risk factors associated with postoperative poor in-hospital prognosis in TBI patients. Multivariate Logistic regression analysis was used to determine independent risk factors and construct a regression equation. The regression equation was presented using R language to create a visual nomogram for predicting postoperative poor in-hospital prognosis in TBI patients. In both the training set and verification set, the predictive performance of the model was evaluated by calculating the area under the receiver operating characteristic (ROC) curve (AUC), plotting calibration curves, and performing decision curve analysis (DCA). Results:The results of the univariate analysis indicated that the age, Charlson complication index (CCI), time from trauma to admission, time from trauma to operation, cause of injury, abbreviated injury scale (AIS) (head and neck), injury severity score (ISS), admission Glasgow coma scale (GCS), admission pupil responsiveness, multiple craniocerebral injuries, subdural hematoma, intracerebral hematoma, intraventricular hemorrhage, subarachnoid hemorrhage, decompressive craniotomy, intraoperative blood loss, intraoperative blood transfusion, traumatic cerebral infarction, postoperative delayed bleeding, epilepsy seizures, as well as the following admission tested results including red blood cell count, white blood cell count, platelet count, neutrophil percentage, percentage of lymphocytes, albumin, total bilirubin, urea nitrogen, thrombin time (TT), prothrombin time (PT), international standardized ratio (INR), glutamic aminotransferase, alanine aminotransferase, creatinine, and blood glucose were statistically different between the two groups in the training set ( P<0.05). Lasso regression analysis suggested 14 risk factors of age, CCI, cause of injury, head and neck AIS, ISS, admission GCS, admission pupil responsiveness, multiple craniocerebral injuries, subdural hematoma, intracerebral hematoma, intraoperative blood loss, admission platelet count, admission albumin, admission blood glucose for postoperative poor in-hospital prognosis. The results of the multivariate Logistic regression analysis showed that age ( OR=1.02, 95% CI 1.00, 1.03, P<0.01), CCI ( OR=1.46, 95% CI 1.02, 2.09, P<0.05), head and neck AIS ( OR=1.43, 95% CI 1.11, 1.85, P<0.01), ISS ( OR=2.16, 95% CI 1.39, 3.35, P<0.01), admission GCS ( OR=1.59, 95% CI 1.19, 2.13, P<0.01), intracerebral hematoma ( OR=4.41, 95% CI 2.15, 9.44, P<0.01), intraoperative blood loss ( OR=1.05, 95% CI 1.00, 1.09, P<0.05), admission platelet count ( OR=0.98, 95% CI 0.97, 0.99, P<0.01), admission blood glucose ( OR=1.08, 95% CI 1.02, 1.15, P<0.05) could be the main risk factors to construct a prediction model for postoperative poor in-hospital prognosis in TBI patients. Meanwhile, a regression equation was constructed: Logit[ P/(1- P)]=-2.4+ 0.02×"age"+0.38×"CCI"+0.36×"head and neck AIS"+0.77×"ISS"+0.47×"admission GCS"+1.48×"intracerebral hematoma"+0.05×intraoperative blood loss-0.02×admission platelet count+0.08×admission blood glucose. In the training set, the predictive model for poor postoperative in-hospital prognosis in TBI patients achieved an AUC of 0.87 (95% CI 0.84, 0.89), with a Youden′s index of 0.57, sensitivity of 73.70%, and specificity of 83.00%. In the verification set, the model showed an AUC of 0.80 (95% CI 0.76, 0.85), with a Youden′s index of 0.63, sensitivity of 65.20%, and specificity of 77.90%. In the training set, the Brier score for the calibration curve was 0.14 (95% CI 0.13, 0.16). In the verification set, the Brier score for the calibration curve was 0.18 (95% CI 0.15, 0.20). The DCA diagram indicated that the nomogram prediction model provided high clinical net benefit for predicting postoperative poor in-hospital prognosis in TBI patients. Conclusion:The prediction model for postoperative poor in-hospital prognosis in TBI patients, constructed based on age, CCI, head and neck AIS, ISS, admission GCS, intracerebral hematoma, intraoperative blood loss, admission platelet count, and admission blood glucose, exhibits good predictive performance.

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.