Traditional Chinese medicine (TCM) represents a paradigmatic approach to personalized medicine, developed through the systematic accumulation and refinement of clinical empirical data over more than 2000 years, and now encompasses large-scale electronic medical records (EMR) and experimental molecular data. Artificial intelligence (AI) has demonstrated its utility in medicine through the development of various expert systems (e.g., MYCIN) since the 1970s. With the emergence of deep learning and large language models (LLMs), AI's potential in medicine shows considerable promise. Consequently, the integration of AI and TCM from both clinical and scientific perspectives presents a fundamental and promising research direction. This survey provides an insightful overview of TCM AI research, summarizing related research tasks from three perspectives: systems-level biological mechanism elucidation, real-world clinical evidence inference, and personalized clinical decision support. The review highlights representative AI methodologies alongside their applications in both TCM scientific inquiry and clinical practice. To critically assess the current state of the field, this work identifies major challenges and opportunities that constrain the development of robust research capabilities-particularly in the mechanistic understanding of TCM syndromes and herbal formulations, novel drug discovery, and the delivery of high-quality, patient-centered clinical care. The findings underscore that future advancements in AI-driven TCM research will rely on the development of high-quality, large-scale data repositories; the construction of comprehensive and domain-specific knowledge graphs (KGs); deeper insights into the biological mechanisms underpinning clinical efficacy; rigorous causal inference frameworks; and intelligent, personalized decision support systems.
Medicine, Chinese Traditional/methods* ; Artificial Intelligence ; Humans ; Precision Medicine ; Decision Support Systems, Clinical

Alzheimer's disease (AD) is a neurodegenerative disease characterized by progressive memory deficits and cognitive decline. Previous studies of peripheral blood biomarkers in AD have been focused on alterations of β-amyloid (Aβ) and phosphorylated (p)-tau. This article reviews the research progress of new biomarkers, such as inflammatory factors, metabolic indicators, and non-coding RNA, in peripheral blood of AD in recent years, in order to provide references for AD diagnosis.

Objective:Cardiac arrest (CA) represents a significant public health challenge, posing a substantial threat to individual health and survival. To enhance the survival rates of patients experiencing out-of-hospital cardiac arrest (OHCA), Baoan District in Shenzhen City has undertaken exploratory initiatives and practical interventions, yielding promising preliminary outcomes.Methods:1.Innovate emergency medical services by developing a "four-circle integration" system that connects to the hospital. This system encompasses the social emergency medical system, the out-of-hospital emergency medical system, the in-hospital emergency medical service system, and the intensive care treatment system. 2.Develop a comprehensive model for the construction of a social emergency medical training system, characterized by party leadership, government oversight, departmental coordination, professional guidance, technological support, and community involvement, termed the "Baonan Model." Additionally, establish evaluation criteria to assess the effectiveness of the social emergency medical training system in Baonan District; 3. Develop a cardiac arrest registration system and a social emergency medical training management system for Baonan District; 4. Enhance the proficiency in treatment techniques and the quality of cardiopulmonary resuscitation among emergency medical professionals; 5. Strengthen and advance the development of a "five-minute social rescue network" to address the critical "emergency window period." .Result:In Baonan District, 9.18% of the public is trained in emergency medical skills. The bystander CPR rate for OHCA is 26.11%, AED use is at 4.78%, the 30-day survival rate is 6.31%, and the discharge survival rate is 4.44%.Conclusion:The implementation of the aforementioned measures can substantially enhance the survival rate of patients experiencing OHCA at the time of discharge.

Objective:To identify diagnostic markers related to oxidative stress in chronic rhinosinusitis with nasal polyps (CRSwNP) by analyzing transcriptome sequencing data, and to investigate their roles in CRSwNP.Methods:Utilizing four CRSwNP sequencing datasets, differentially expressed genes (DEGs) analysis, weighted gene co-expression network analysis (WGCNA), and three machine learning methods for Hub gene selection were performed in this study. Subsequent validation was carried out using external datasets, as well as real-time quantitative polymerase chain reaction (Real-time qPCR), and immunofluorescence staining of clinical samples. Moreover, the diagnostic efficacy of the genes was assessed by receiver operating characteristic (ROC) curve, followed by functional and pathway enrichment analysis, immune-related analysis, and cell population localization. Additionally, a competing endogenous RNA (CeRNA) network was constructed to predict potential drug targets. Statistical analysis and plotting were conducted using SPSS 26.0 and Graphpad Prism9 software.Results:Through data analysis and clinical validation, CP, SERPINF1 and GSTO2 were identified among 4 138 DEGs as oxidative stress markers related to CRSwNP. Specifically, the expression of CP and SERPINF1 increased in CRSwNP, whereas that of GSTO2 decreased, with statistically significant differences ( P<0.05). Additionally, an area under the curve (AUC)>0.7 indicated their effectiveness as diagnostic indicators. Importantly, functional analysis indicated that these genes were mainly related to lipid metabolism, cell adhesion migration, and immunity. Single-cell data analysis revealed that SERPINF1 was mainly distributed in epithelial cells, stromal cells, and fibroblasts, while CP was primarily located in epithelial cells, and GSTO2 was minimally present in the epithelial cells and fibroblasts of nasal polyps. Consequently, a CeRNA regulatory network was constructed for the genes CP and GSTO2. This construction allowed for the prediction of potential drugs that could target CP. Conclusion:This study successfully identifies CP, SERPINF1 and GSTO2 as diagnostic and therapeutic markers related to oxidative stress in CRSwNP.

In 2009,the World Health Organization included snakebite on the list of neglected tropical diseases,acknowledging it as a common occupational hazard for farmers,plantation workers,and others,causing tens of thousands of deaths and chronic physical disabilities every year.This guideline aims to provide practical information to help clinical professionals evaluate and treat snakebite victims.These recommendations are based on clinical experience and clinical research evidence.This guideline focuses on the following topics:snake venom,clinical manifestations,auxiliary examination,diagnosis,treatments,and prevention.

OBJECTIVE To reveal the pharmacological mechanism of Sofren Injection in the treatment of Qi deficiency and blood stasis syndrome of angina pectoris in coronary heart disease,and to preliminarily verify the reliability of the prediction results by cell experiments.METHODS Firstly,we screened the main chemical components of Sofren injection and their targets from biomedical databases and literature.Then,using the DIAMOnD algorithm,we constructed the angina disease module by screening Qi deficiency and blood stasis syndrome-related genes from the GeneCards and MalaCards databases.Next,we conducted gene functional enrichment analysis of the core targets in the"angina pectoris-Qi deficiency and blood stasis-Sofren Injection"network to identify key pathways.Finally,we performed cell experiments to verify the effect of Sofren Injection on the expression of key pathway proteins in hypoxic H9C2 cardiomyocytes.RESULTS We identified 7 main chemical components of Sofren Injection,targeting a total of 362 genes.We screened 232 known angina pectoris-related genes and added 100 predicted genes by constructing the angina pectoris dis-ease module.A total of 2 960 genes related to Qi deficiency and blood stasis syndrome were obtained.Network topological analysis re-vealed 30 core targets for Sofren Injection in treating coronary heart disease angina pectoris with Qi deficiency and blood stasis syn-drome,including STAT3,EGFR,TNF,and IL-6.Gene functional enrichment analysis identified 82 pathways.Literature analysis combined with the results indicated that STAT3 and the JAK2/STAT3 pathway might be key pathways for Sofren Injection in treating coronary heart disease angina pectoris with Qi deficiency and blood stasis syndrome.Cell experimental results showed significant de-creases in mRNA and protein expression of JAK2 and STAT3 in the SI group and the nicorandil group compared to the model group(P<0.05).CONCLUSION Disease module analysis and cell experiments confirm that STAT3 is a key gene in the pathological mecha-nism of coronary heart disease angina pectoris with Qi deficiency and blood stasis syndrome,and the JAK2/STAT3 pathway is a core pathway for Sofren Injection in treating this condition.This study demonstrates the effectiveness and novelty of combining disease mod-ule for mining the treatment of TCM formulas with specific disease and syndrome.

Objective To develop and evaluate a fine-tuned large language model(LLM)for traditional Chinese medicine(TCM)prescription recommendation named TCMLLM-PR.Methods First,we constructed an instruction-tuning dataset containing 68 654 samples(ap-proximately 10 million tokens)by integrating data from eight sources,including four TCM textbooks,Pharmacopoeia of the People's Republic of China 2020(CHP),Chinese Medicine Clinical Cases(CMCC),and hospital clinical records covering lung disease,liver disease,stroke,diabetes,and splenic-stomach disease.Then,we trained TCMLLM-PR using Chat-GLM-6B with P-Tuning v2 technology.The evaluation consisted of three aspects:(i)compari-son with traditional prescription recommendation models(PTM,TCMPR,and PresRecST);(ii)comparison with TCM-specific LLMs(ShenNong,Huatuo,and HuatuoGPT)and general-domain ChatGPT;(iii)assessment of model migration capability across different disease datasets.We employed precision,recall,and F1 score as evaluation metrics.Results The experiments showed that TCMLLM-PR significantly outperformed baseline models on TCM textbooks and CHP datasets,with F1@10 improvements of 31.80%and 59.48%,respectively.In cross-dataset validation,the model performed best when migrating from TCM textbooks to liver disease dataset,achieving an F1@10 of 0.155 1.Analysis of real-world cases demonstrated that TCMLLM-PR's prescription recommendations most closely matched actual doctors'prescriptions.Conclusion This study integrated LLMs into TCM prescription recommendations,leverag-ing a tailored instruction-tuning dataset and developing TCMLLM-PR.This study will pub-licly release the best model parameters of TCMLLM-PR to promote the development of the decision-making process in TCM practices(https://github.com/2020MEAI/TCMLLM).

OBJECTIVE To reveal the pharmacological mechanism of Sofren Injection in the treatment of Qi deficiency and blood stasis syndrome of angina pectoris in coronary heart disease,and to preliminarily verify the reliability of the prediction results by cell experiments.METHODS Firstly,we screened the main chemical components of Sofren injection and their targets from biomedical databases and literature.Then,using the DIAMOnD algorithm,we constructed the angina disease module by screening Qi deficiency and blood stasis syndrome-related genes from the GeneCards and MalaCards databases.Next,we conducted gene functional enrichment analysis of the core targets in the"angina pectoris-Qi deficiency and blood stasis-Sofren Injection"network to identify key pathways.Finally,we performed cell experiments to verify the effect of Sofren Injection on the expression of key pathway proteins in hypoxic H9C2 cardiomyocytes.RESULTS We identified 7 main chemical components of Sofren Injection,targeting a total of 362 genes.We screened 232 known angina pectoris-related genes and added 100 predicted genes by constructing the angina pectoris dis-ease module.A total of 2 960 genes related to Qi deficiency and blood stasis syndrome were obtained.Network topological analysis re-vealed 30 core targets for Sofren Injection in treating coronary heart disease angina pectoris with Qi deficiency and blood stasis syn-drome,including STAT3,EGFR,TNF,and IL-6.Gene functional enrichment analysis identified 82 pathways.Literature analysis combined with the results indicated that STAT3 and the JAK2/STAT3 pathway might be key pathways for Sofren Injection in treating coronary heart disease angina pectoris with Qi deficiency and blood stasis syndrome.Cell experimental results showed significant de-creases in mRNA and protein expression of JAK2 and STAT3 in the SI group and the nicorandil group compared to the model group(P<0.05).CONCLUSION Disease module analysis and cell experiments confirm that STAT3 is a key gene in the pathological mecha-nism of coronary heart disease angina pectoris with Qi deficiency and blood stasis syndrome,and the JAK2/STAT3 pathway is a core pathway for Sofren Injection in treating this condition.This study demonstrates the effectiveness and novelty of combining disease mod-ule for mining the treatment of TCM formulas with specific disease and syndrome.

Objective To develop and evaluate a fine-tuned large language model(LLM)for traditional Chinese medicine(TCM)prescription recommendation named TCMLLM-PR.Methods First,we constructed an instruction-tuning dataset containing 68 654 samples(ap-proximately 10 million tokens)by integrating data from eight sources,including four TCM textbooks,Pharmacopoeia of the People's Republic of China 2020(CHP),Chinese Medicine Clinical Cases(CMCC),and hospital clinical records covering lung disease,liver disease,stroke,diabetes,and splenic-stomach disease.Then,we trained TCMLLM-PR using Chat-GLM-6B with P-Tuning v2 technology.The evaluation consisted of three aspects:(i)compari-son with traditional prescription recommendation models(PTM,TCMPR,and PresRecST);(ii)comparison with TCM-specific LLMs(ShenNong,Huatuo,and HuatuoGPT)and general-domain ChatGPT;(iii)assessment of model migration capability across different disease datasets.We employed precision,recall,and F1 score as evaluation metrics.Results The experiments showed that TCMLLM-PR significantly outperformed baseline models on TCM textbooks and CHP datasets,with F1@10 improvements of 31.80%and 59.48%,respectively.In cross-dataset validation,the model performed best when migrating from TCM textbooks to liver disease dataset,achieving an F1@10 of 0.155 1.Analysis of real-world cases demonstrated that TCMLLM-PR's prescription recommendations most closely matched actual doctors'prescriptions.Conclusion This study integrated LLMs into TCM prescription recommendations,leverag-ing a tailored instruction-tuning dataset and developing TCMLLM-PR.This study will pub-licly release the best model parameters of TCMLLM-PR to promote the development of the decision-making process in TCM practices(https://github.com/2020MEAI/TCMLLM).

The thalamocortical (TC) circuit is closely associated with pain processing. The hyperpolarization-activated cyclic nucleotide-gated (HCN) 2 channel is predominantly expressed in the ventral posterolateral thalamus (VPL) that has been shown to mediate neuropathic pain. However, the role of VPL HCN2 in modulating TC circuit activity is largely unknown. Here, by using optogenetics, neuronal tracing, electrophysiological recordings, and virus knockdown strategies, we showed that the activation of VPL TC neurons potentiates excitatory synaptic transmission to the hindlimb region of the primary somatosensory cortex (S1HL) as well as mechanical hypersensitivity following spared nerve injury (SNI)-induced neuropathic pain in mice. Either pharmacological blockade or virus knockdown of HCN2 (shRNA-Hcn2) in the VPL was sufficient to alleviate SNI-induced hyperalgesia. Moreover, shRNA-Hcn2 decreased the excitability of TC neurons and synaptic transmission of the VPL-S1HL circuit. Together, our studies provide a novel mechanism by which HCN2 enhances the excitability of the TC circuit to facilitate neuropathic pain.
Animals ; Mice ; Hyperpolarization-Activated Cyclic Nucleotide-Gated Channels/genetics* ; Neuralgia ; RNA, Small Interfering ; Thalamus/metabolism* ; Up-Regulation