Objective To evaluate the efficacy of combining the replenishing qi and nourishing yin empirical formula with anti-vascular endothelial growth factor (VEGF) in diabetic macular edema (DME). Methods A retrospective analysis was conducted on 59 patients diagnosed with DME at Tongji Hospital of Tongji University or Shanghai Nanxiang Hospital, Jiading District from June 2019 to December 2022. Among them, 29 cases received intravitreal injection of ranibizumab (anti-VEGF group), while 30 cases received both intravitreal injection of ranibizumab and oral administration of the replenishing qi and nourishing yin empirical formula (combined treatment group). The best corrected visual acuity (BCVA), central macular thickness (CMT), and the traditional Chinese medicine (TCM) syndrome score were compared between the two groups before treatment and at 4, 8, 12, 16, 20, and 24 weeks after treatment. Results Compared with before treatment, BCVA significantly improved (P＜0.05) and CMT significantly decreased (P＜0.05) at different time points after treatment in both groups. At 16, 20, and 24 weeks after treatment, BCVA in the combined treatment group was superior to that in the anti-VEGF group (P＜0.01). At 12, 16, 20, and 24 weeks after treatment, CMT in the combined treatment group was lower than that in the anti-VEGF group (P＜0.01). Starting from week 8 after treatment, the TCM syndrome scores in the combined treatment group were lower than those in the anti-VEGF group (P＜0.01). Conclusions The replenishing qi and nourishing yin empirical formula could improve the efficacy of anti-VEGF therapy in DME patients, indicating that integrating traditional Chinese and Western medicine has certain clinical application value in treating DME.

Objective: To evaluate the application value of a digital technology-based multiparameter vital signs monitoring system in perioperative comprehensive full-cycle surveillance. Methods: A comprehensive multidimensional vital signs monitoring system was developed through the integration of medical-grade wireless wearable devices, incorporating patch-type ambulatory electrocardiographic monitor, continuous glucose monitoring sensor, pulse oximeter, wireless digital thermometer, smart wristband, and bioelectrical impedance analyzer. This system facilitates continuous real-time acquisition of multiple physiological parameters including electrocardiogram, blood glucose, oxygen saturation, body temperature, physical activity, and body composition indices. The acquired data were systematically integrated and analyzed through a four-level digital architecture consisting of nurse mobile interfaces, bedside patient terminals, centralized ward monitoring displays, and hospital management information systems. One patient with gastric cancer complicated by diabetes mellitus was selected for full-cycle digital monitoring from preoperative evaluation to hospital discharge. The technical performance of the monitoring system was assessed in terms of data acquisition continuity and timeliness of abnormal event alerts. Results: The monitoring system effectively identified early postoperative abnormalities, such as decreased oxygen saturation and blood glucose fluctuations, providing timely guidance for clinical intervention. The built-in algorithm enabled visualization of perioperative stress levels through heart rate variability indices and continuous glucose monitoring data. The patient demonstrated good compliance with early postoperative mobilization, and the satisfaction score for monitoring management was 4 points based on the Likert 5-point scale. Conclusions: The multiparameter vital signs monitoring system enhanced the precision of perioperative management through continuous and dynamic physiological status assessment. Its modular design aligns with the principles of enhanced recovery after surgery, offering a novel technological solution for intelligent perioperative management.
Humans ; Stomach Neoplasms/physiopathology* ; Vital Signs ; Monitoring, Physiologic/instrumentation* ; Diabetes Mellitus ; Wearable Electronic Devices ; Perioperative Period

Gelsemium elegans (G. elegans) is an extremely poisonous plant that is widely distributed in southern China and southeastern Asia. G. elegans poisoning events occur frequently in southern China, and are therefore an urgent public health problem requiring multidisciplinary action. However, the toxic components and toxicological mechanisms remain unclear. Here, we describe a systematic investigation on the toxic components of G. elegans, resulting in the isolation and identification of 120 alkaloids. Based on acute toxicity screening, the structure-toxicity relationship of Gelsemium alkaloids was proposed for the first time. Moreover, gelsedine- and humantenine-type alkaloids were detected in the clinical blood sample, and were confirmed to be causative in the poisoning. The most toxic compound, gelsenicine (1), had selective inhibitory effects toward ventral respiratory group (VRG) neurons in the medulla, which is the main brain region controlling respiration in the central nervous system. Gelsenicine (1) strongly inhibited the firing of action potentials in VRG neurons through its ability to stimulate GABA_A receptors, the main receptors involved in inhibitory neurotransmission. Application of GABA_A receptor antagonists successively reversed action potential firing in gelsenicine (1)-treated VRG neurons. Importantly, the GABA_A receptor antagonists securinine and flumazenil significantly increased the survival of poisoned animals. Our findings provide insight into the components and mechanisms of G. elegans toxicity, and should assist the development of effective emergency treatments for G. elegans poisoning.

Objective To construct an innovative CNN-Transformer dual-stream parallel network architecture integrating clinical data and imaging features for improving the predictive accuracy of pectoralis major myofascial metastasis in breast cancer,and to optimize the model performance by screening the optimal feature subset through genetic algorithm.Methods The proposed architecture concurrently processed clinical records and imaging data,including physical characteristics such as resolution,contrast,grayscale distribution,and texture features to identify their latent correlations.Meanwhile,genetic algorithms were employed to remove redundant features while retaining the most clinically and physically relevant features for pectoralis major myofascial metastasis prediction.Results The CNN-Transformer model that integrated imaging and clinical features showed superior performance across all evaluation metrics such as weighted F1 score and AUCROC,outperforming models relying only on imaging or clinical data.Conclusion The proposed dual-stream parallel network architecture combined with feature selection strategy significantly enhances the predictive accuracy of pectoralis major myofascial metastasis in breast cancer,and demonstrates the critical role of imaging features in improving model performance.

Under the guidance of China′s national innovation-driven development strategy, advancing the deep integration of industry-academia-research in the healthcare sector has become a crucial pathway for enhancing medical technology levels and promoting high-quality development of hospitals. In 2021, Peking University Third Hospital established a hospital-enterprise joint research and development platform centered on hospital leadership, grounded in collaborative innovation theory. By translating the theoretical principles of " goal alignment, resource complementarity, risk sharing, and benefit sharing" into a multidimensional institutional framework, dynamic consensus mechanisms, and specialized support systems, the hospital developed a multi-tiered implementation pathway of " strategic guidance-platform implementation-research and development deployment". This approach enabled precise matching of resources and needs, efficiently advancing the innovation, transformation, and application of medical technologies. By the end of 2024, the platform had established stable partnerships with 22 enterprises, cumulatively undertaken 123 clinical research projects, as well as achieved a series of breakthroughs in fields such as cell therapy and intelligent imaging. This platform could solve problems such as divergent goals and institutional deficiencies in traditional medical enterprise cooperation, which could help to form a good innovation ecosystem and provide reference and inspiration for the construction of China′s medical technology innovation system.

Objective:To explore the effective way to improve the protection efficiency of intellectual property rights of medical institutions in the field of biomedicine by building an efficient patent pre-examination management system, so as to promote the transformation of achievements.Methods:Through literature review, case analysis and combined with the actual examination situation of the intellectual property protection center, the study analyzed and summarized the characteristics of long R&D cycle, rapid technology iteration, multidisciplinary intersection in the field of biomedicine, and the necessity of hospitals to carry out patent pre-examination work.Results:The pre-examination awareness of scientific researchers in medical institutions was weak, the drafting of application documents was not standardized, and the patent achievements were out of touch with the market.Conclusions:To accelerate intellectual property conversion of innovation achievements, innovation management strategies should be implemented: standardized processes, pre-evaluation, professional team support, process control and talent cultivation.

Fatty liver is common disease of nutritional metabolism in the perinatal period,character-ized by elevated levels of NEFA in the blood and disorders of lipid metabolism.High concentra-tions of NEFA damage mitochondria and promote the release of reactive oxygen species(ROS).At the same time,lipid peroxidation occurs in lipid accumulation in hepatocytes,producing free radi-cals such as ROS,which leads to oxidative stress in the liver.When the level of intracellular ROS increases,thioredoxin-interacting protein(TXNIP)activates nucleotide-binding oligomerization structure-like protein 3(NLRP3)inflammasomes,and oxidative stress can regulate pyroptosis,but it is unclear whether reactive oxygen species(ROS)produced by oxidative stress in hepatocytes can mediate pyroptosis and induce liver injury in dairy cows through the TXNIP/NLRP3 pathway.In this study,liver tissue samples from healthy dairy cows and fatty liver cows were collected,and NEFA was used to construct a fatty liver cell model,and triglyceride(TG)content and oxidative stress related indicators were detected by kit.Western blot was used to detect the activation of NL-RP3 inflammasomes,the inflammatory pathway of NF-κB and the expression levels of pyroptosis-related proteins.Fluorescence quantitative PCR was used to detect the relative expression level of inflammatory factor mRNA.The results showed that compared with the healthy(control)group,the TG content of fatty liver tissue and fatty liver cells was significantly increased(P＜0.05),the activities of SOD and GSH-Px were significantly decreased(P＜0.05),and the protein expression levels of TXNIP,NLRP3,GSDMD-N and Caspase-1 were significantly up-regulated(P＜0.05).The results of the antioxidant model of fatty hepatocytes using NEFA and antioxidants(NAC)showed that compared with the fatty hepatocyte model,the content of ROS in hepatocytes was sig-nificantly reduced,and oxidative stress,NLRP3 inflammasome activation and pyroptosis were alle-viated.In summary,this study found that when fatty liver disease occurs in dairy cows,ROS pro-duced by oxidative stress in the liver can mediate pyroptosis through the TXNIP/NLRP3 path-way,which can lead to liver injury in fatty liver cows.

Objective To construct an innovative CNN-Transformer dual-stream parallel network architecture integrating clinical data and imaging features for improving the predictive accuracy of pectoralis major myofascial metastasis in breast cancer,and to optimize the model performance by screening the optimal feature subset through genetic algorithm.Methods The proposed architecture concurrently processed clinical records and imaging data,including physical characteristics such as resolution,contrast,grayscale distribution,and texture features to identify their latent correlations.Meanwhile,genetic algorithms were employed to remove redundant features while retaining the most clinically and physically relevant features for pectoralis major myofascial metastasis prediction.Results The CNN-Transformer model that integrated imaging and clinical features showed superior performance across all evaluation metrics such as weighted F1 score and AUCROC,outperforming models relying only on imaging or clinical data.Conclusion The proposed dual-stream parallel network architecture combined with feature selection strategy significantly enhances the predictive accuracy of pectoralis major myofascial metastasis in breast cancer,and demonstrates the critical role of imaging features in improving model performance.

Fatty liver is common disease of nutritional metabolism in the perinatal period,character-ized by elevated levels of NEFA in the blood and disorders of lipid metabolism.High concentra-tions of NEFA damage mitochondria and promote the release of reactive oxygen species(ROS).At the same time,lipid peroxidation occurs in lipid accumulation in hepatocytes,producing free radi-cals such as ROS,which leads to oxidative stress in the liver.When the level of intracellular ROS increases,thioredoxin-interacting protein(TXNIP)activates nucleotide-binding oligomerization structure-like protein 3(NLRP3)inflammasomes,and oxidative stress can regulate pyroptosis,but it is unclear whether reactive oxygen species(ROS)produced by oxidative stress in hepatocytes can mediate pyroptosis and induce liver injury in dairy cows through the TXNIP/NLRP3 pathway.In this study,liver tissue samples from healthy dairy cows and fatty liver cows were collected,and NEFA was used to construct a fatty liver cell model,and triglyceride(TG)content and oxidative stress related indicators were detected by kit.Western blot was used to detect the activation of NL-RP3 inflammasomes,the inflammatory pathway of NF-κB and the expression levels of pyroptosis-related proteins.Fluorescence quantitative PCR was used to detect the relative expression level of inflammatory factor mRNA.The results showed that compared with the healthy(control)group,the TG content of fatty liver tissue and fatty liver cells was significantly increased(P＜0.05),the activities of SOD and GSH-Px were significantly decreased(P＜0.05),and the protein expression levels of TXNIP,NLRP3,GSDMD-N and Caspase-1 were significantly up-regulated(P＜0.05).The results of the antioxidant model of fatty hepatocytes using NEFA and antioxidants(NAC)showed that compared with the fatty hepatocyte model,the content of ROS in hepatocytes was sig-nificantly reduced,and oxidative stress,NLRP3 inflammasome activation and pyroptosis were alle-viated.In summary,this study found that when fatty liver disease occurs in dairy cows,ROS pro-duced by oxidative stress in the liver can mediate pyroptosis through the TXNIP/NLRP3 path-way,which can lead to liver injury in fatty liver cows.

Under the guidance of China′s national innovation-driven development strategy, advancing the deep integration of industry-academia-research in the healthcare sector has become a crucial pathway for enhancing medical technology levels and promoting high-quality development of hospitals. In 2021, Peking University Third Hospital established a hospital-enterprise joint research and development platform centered on hospital leadership, grounded in collaborative innovation theory. By translating the theoretical principles of " goal alignment, resource complementarity, risk sharing, and benefit sharing" into a multidimensional institutional framework, dynamic consensus mechanisms, and specialized support systems, the hospital developed a multi-tiered implementation pathway of " strategic guidance-platform implementation-research and development deployment". This approach enabled precise matching of resources and needs, efficiently advancing the innovation, transformation, and application of medical technologies. By the end of 2024, the platform had established stable partnerships with 22 enterprises, cumulatively undertaken 123 clinical research projects, as well as achieved a series of breakthroughs in fields such as cell therapy and intelligent imaging. This platform could solve problems such as divergent goals and institutional deficiencies in traditional medical enterprise cooperation, which could help to form a good innovation ecosystem and provide reference and inspiration for the construction of China′s medical technology innovation system.