Objective To investigate the mechanism and optimal concentration of anrotinib on ovarian clear cell carcinoma.Methods Ovarian clear cell carcinoma cells were cultured in vitro,by using renal clear cell carcinoma cells and renal papillary cell carcinoma cells as control cancer cells,and the effects of different concentrations of anlotinib(5,10,15,20μmol/L)on the proliferation,migration,and invasion capabilities of three cancer cell lines were investigated.Compared with the experimental results of renal clear cell carcinoma cells and renal papillary cell carcinoma cells,the advantages of anlotinib on ovarian clear cell carcinoma cells were investigated and advanced its position in clinical practice.Results Anlotinib at the concentrations of 5,10,15,and 20μmol/L can effectively inhibit the proliferation,migration,and invasion ability of ovarian clear cell carcinoma cells,renal clear cell carcinoma cells,and renal papillary cell carcinoma cells.Among them,the optimal action concentration of anlotinib on all three cancer cells fell in the range of 5-10 μmol/L.However,in the three cancer cells,anlotinib was more potent in ovarian clear cell carcinoma cells.Conclusion The effect of anlotinib on ovarian clear cell carcinoma cells has obvious advantages over renal clear cell carcinoma cells and renal papillary cell carcinoma cells,with the optimal concentration of 5-10 μmol/L.

Objective To investigate the mechanism and optimal concentration of anrotinib on ovarian clear cell carcinoma.Methods Ovarian clear cell carcinoma cells were cultured in vitro,by using renal clear cell carcinoma cells and renal papillary cell carcinoma cells as control cancer cells,and the effects of different concentrations of anlotinib(5,10,15,20μmol/L)on the proliferation,migration,and invasion capabilities of three cancer cell lines were investigated.Compared with the experimental results of renal clear cell carcinoma cells and renal papillary cell carcinoma cells,the advantages of anlotinib on ovarian clear cell carcinoma cells were investigated and advanced its position in clinical practice.Results Anlotinib at the concentrations of 5,10,15,and 20μmol/L can effectively inhibit the proliferation,migration,and invasion ability of ovarian clear cell carcinoma cells,renal clear cell carcinoma cells,and renal papillary cell carcinoma cells.Among them,the optimal action concentration of anlotinib on all three cancer cells fell in the range of 5-10 μmol/L.However,in the three cancer cells,anlotinib was more potent in ovarian clear cell carcinoma cells.Conclusion The effect of anlotinib on ovarian clear cell carcinoma cells has obvious advantages over renal clear cell carcinoma cells and renal papillary cell carcinoma cells,with the optimal concentration of 5-10 μmol/L.

Purpose/Significance To construct a named entity corpus of traditional Chinese medicine(TCM)ancient records,and to improve the recognition accuracy and applicability of the general domain named entity recognition(NER)model in the field of TCM ancient records.Method/Process Annotation standards for entities in TCM ancient records are formulated,and 2 384 Xin'an medical records are annotated.A RoBERTa-BiLSTM-CRF model is developed,and word vectors with semantic features are generated using the RoBERTa pre-trained language model.The BiLSTM-CRF model is used to learn the global semantic features of sequences and decode and output the optimal label sequence.Dictionary and rule features are incorporated to enhance the model's capability to recognize entity boundaries and categories.Result/Conclusion The model shows a good recognition effect on the named entity corpus of Xin'an medical cases.Integration of domain terminology dictionaries and rule-based features improves the overall Fl score to 72.8％.

OBJECTIVE To develop an artificial intelligence-based intelligent auxiliary diagnosis and treatment system for Xin'an medicine to address the challenges of integrating ancient Xin'an medical case records into modern clinical applications.METHODS The project involved structuring and standardizing case records from ancient texts of Xin'an medicine to build a compre-hensive Xin'an medicine database.Advanced techniques,such as data annotation,entity relationship extraction,and data mining,were applied to create a Xin'an medicine knowledge base.Furthermore,a knowledge graph of Xin'an medicine was constructed using techniques for knowledge acquisition,integration,storage,and graph-based question-answering,improving the efficiency of knowl-edge organization and retrieval.The LangChain framework was utilized to connect the Xin'an medicine knowledge base to a large lan-guage model,enabling a model-driven local knowledge base question-answering system.RESULTS The study successfully estab-lished a systematic and standardized knowledge base for Xin'an medical case records.The application of knowledge graph technology provided a clear visualization of Xin'an medicine's knowledge structure,and the development of an intelligent question-answering module significantly improved the efficiency of knowledge management and retrieval.The local knowledge base question-answering sys-tem,powered by a large language model and based on Xin'an medicine's theoretical and practical expertise,delivered accurate diag-nostic and treatment support,promoting the heritage and innovation of Xin'an medicine.CONCLUSION This research validates the feasibility of modernizing traditional medical texts and provides an innovative approach to knowledge development and clinical applica-tion in Chinese medicine.The findings have significant academic value and promising clinical implications.

OBJECTIVE To develop an artificial intelligence-based intelligent auxiliary diagnosis and treatment system for Xin'an medicine to address the challenges of integrating ancient Xin'an medical case records into modern clinical applications.METHODS The project involved structuring and standardizing case records from ancient texts of Xin'an medicine to build a compre-hensive Xin'an medicine database.Advanced techniques,such as data annotation,entity relationship extraction,and data mining,were applied to create a Xin'an medicine knowledge base.Furthermore,a knowledge graph of Xin'an medicine was constructed using techniques for knowledge acquisition,integration,storage,and graph-based question-answering,improving the efficiency of knowl-edge organization and retrieval.The LangChain framework was utilized to connect the Xin'an medicine knowledge base to a large lan-guage model,enabling a model-driven local knowledge base question-answering system.RESULTS The study successfully estab-lished a systematic and standardized knowledge base for Xin'an medical case records.The application of knowledge graph technology provided a clear visualization of Xin'an medicine's knowledge structure,and the development of an intelligent question-answering module significantly improved the efficiency of knowledge management and retrieval.The local knowledge base question-answering sys-tem,powered by a large language model and based on Xin'an medicine's theoretical and practical expertise,delivered accurate diag-nostic and treatment support,promoting the heritage and innovation of Xin'an medicine.CONCLUSION This research validates the feasibility of modernizing traditional medical texts and provides an innovative approach to knowledge development and clinical applica-tion in Chinese medicine.The findings have significant academic value and promising clinical implications.

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.