Background: Diabetic peripheral neuropathy (DPN) is a common chronic complication of diabetes mellitus that significantly impairs patients’ quality of life. Traditional Chinese medicine (TCM), as a major component of complementary and alternative medicine, has accumulated numerous effective formulas for the clinical management of DPN. However, systematic approaches for optimizing TCM formulas remain limited. Objective: To establish a pathway-oriented approach for TCM formula optimization and to evaluate the efficacy and mechanisms of the optimized formula in DPN. Methods: We developed 2 formula optimization algorithms that defined pathway-oriented herbal correlation (HC) and herbal contribution (HO) to screen and construct a new herbal formula, Qihongtongbi (QHTB), for treating Qi deficiency and blood stasis syndrome complicated with DPN. An animal experiment was subsequently conducted to evaluate the therapeutic effectiveness of QHTB. A total of 32 specific-pathogen-free male ob/ob mice (18–20 g) were randomly divided into 4 groups: model, Mudan Granules (MDG), QHTB low- and high-dose groups (n = 8). Ten male C57BL/6J mice (18–20 g) served as the control group. Metabolomics analysis was further employed to elucidate the biological mechanisms underlying the effects of QHTB. Results: Based on our previous study on TCM medication patterns for treating DPN, 22 candidate herbs were selected for formula optimization. The top 5 candidate herbs (total HC = 25.24 × 10 ) exhibited HC values comparable to those of MDG (total HC = 26.1 × 10 ). These herbs were Carthamus tinctorius L. (HC = 5.40 × 10 ), Astragalus mongholicus Bunge (HC = 5.23 × 10 ), Salvia miltiorrhiza Bunge (HC = 5.15 × 10 ), Commiphora myrrha (T. Nees) Engl. (HC = 5.02 × 10 ), and Glycyrrhiza glabra L. (HC = 4.44 × 10 ). HO analysis showed that the cumulative HO of these 5 herbs exceeded 50%. In vivo experiments demonstrated that, compared with the model group, QHTB significantly lowered blood glucose (P < 0.05), enhanced nerve conduction velocity (P < 0.01), improved nociceptive hypersensitivity (P < 0.01), and ameliorated sciatic nerve morphology, with efficacy comparable to MDG. Serum and fecal metabolomics further revealed that QHTB exerted multipathway regulatory effects, among which nicotinate and nicotinamide metabolism represented a key mechanism. Conclusion: In summary, this study provides a methodological reference for the systematic optimization of TCM formulas.

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

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).

Objective:To collect and analyze laboratory indicators of patients of different sexes after blood transfusion, evaluate the effectiveness of blood transfusion, and provide a theoretical basis for formulating more scientific blood transfusion plans.Methods:The clinical data of 808 patients who underwent blood transfusion in The First Affiliated Hospital of Anhui University of Science and Technology from January 2020 to December 2021 were retrospectively analyzed. According to the blood transfusion strategy and the department to which the patients were admitted, these patients were divided into four groups: surgical restrictive blood transfusion group (group A: 72 males and 69 females), surgical non-restricted blood transfusion (group B: 77 males and 118 females), medical restrictive blood transfusion (group C: 184 males and 126 females), and medical non-restricted blood transfusion (group D: 110 males and 52 females). Univariate and multivariate Logistic regression analyses were performed.Results:In group A, after blood transfusion, hemoglobin level in female patients was significantly higher than that in male patients [79.0 (71.5, 87.0) g/L vs. 75.5 (69.0, 82.8) g/L, Z = -2.18, P = 0.029], and C-reactive protein in female patients was significantly lower than that in male patients [21.3 (0.0, 56.0) mg/L vs. 37.0 (3.3, 95.5) mg/L, Z = -1.97, P = 0.049]. In groups B, C, and D, there were no significant differences in hemoglobin, C-reactive protein, and hematocrit between male and female patients (all P > 0.05). Multivariate analysis showed that the difference in hemoglobin levels between before and after blood transfusion was statistically significant ( P = 0.009). After a blood transfusion, hemoglobin level in female patients was 1.44 times that in male patients. Conclusion:The tolerance of female patients to blood loss is higher than that of male patients in surgical restrictive blood transfusion, so the threshold value of hemoglobin given to female patients during blood transfusion can be lower than that of male patients. In the case of the same blood loss, priority of blood transfusion can be given to male patients. In the case of scarce blood resources, the total amount of blood transfused for female patients can be approximately reduced.

Objective:To explore the therapeutic characteristics of population with gout achieving treat-to-target (T2T) indicators through real-world research and evaluate their safety.Methods:A total of 3 287 patients diagnosed with gout by rheumatologists in 21 first-class tertiary hospitals in 10 provinces, municipalities, and autonomous regions in China from January 2015 to December 2021 were included in this polycentric cross-sectional study. The database included patients′ general information, disease characteristics, and clinical application of traditional Chinese and Western medicine treatment measures. SPSS and Excel software were used for data analysis. Frequency analysis, cluster analysis, and factor analysis were used to summarize the characteristics and rules of treatment measures for patients with gout who achieved the target after treatment. The occurrence of adverse events (AE) was recorded during treatment.Results:After treatment, 691 visits (7%) achieved the serum urate (SUA) target, and the most frequent use of urate-lowering therapy (ULT) was febuxostat, followed by benzbromarone. The most common treatment options were following: GroupⅠ: traditional Chinese medicine (TCM) decoction-TCM external treatment-physical exercise-proprietary Chinese medicine; GroupⅡ: ferulic acid-nonsteroidal anti-inflammatory drugs (NSAIDs); Group Ⅲ: allopurinol-sodium bicarbonate-benzbromarone; Group Ⅳ: glucocorticoid-colchicine; Group Ⅴ: febuxostat. A total of 5 898 visits (60%) chieved manifestations of joint pain VAS scores target, and the most frequently used drug to control joint symptoms was NSAIDs. The frequency of use of drugs to control joint symptoms were 2 118 times (usage rate reached 35.9%), while the frequency of ULT were 2 504 times (usage rate reached 42.5%), which was higher than the joint symptom control drug. The most common treatment options were following: Group Ⅰ: proprietary Chinese medicine-TCM decoction-TCM external treatment-physical exercise; Group Ⅱ: NSAIDs-colchicine hormones; Group Ⅲ: allopurinol, Group Ⅳ: benzbromarone; Group Ⅴ: febuxostat. A total of 59 adverse events occurred during treatment.Conclusion:The proportions of gout patients who reach target serum urate level & good control of joint symptoms are both very low, and ULT and anti-inflammatory prescription patterns are very different from international guidelines, so it is necessary to strengthen the standardized management of gout patients. At the same time, life intervention measures account for a certain proportion of the treatment plans for the T2T population, and further exploration is needed.

Objective:To investigate the relationship between previous bleeding history and poor prognosis of patients with acute upper gastrointestinal bleeding.Methods:This study was a prospective multicentre real-world study (Acute Upper Gastrointestinal Real-word study, AUGUR study). The data of patients with UGIB who were admitted to the emergency department of 20 tertiary hospitals in China from June 30, 2020 to February 10, 2021 were collected. According to the number of previous bleeding history, the patients were divided into three groups (0 time, 1-3 times, and≥4 times). Based on the patient’s demographic data, clinical characteristics, laboratory data, treatment, and outcomes, univariate and logistic regression analysis were performed to investigate the correlation between the number of previous bleeding and the 90-day mortality and rebleeding of patients with gastrointestinal bleeding.Results:A total of 1 072 patients with acute UGIB were included in this study. The all-cause mortality and rebleeding rate of all patients were 10.9% (117/1 072) and 11.8% (129/1 072), respectively. Among them, 712 patients (66.42%) had no previous bleeding, 297 patients (27.71%) had previous bleeding 1-3 times, and 63 patients (5.88%) had previous bleeding≥4 times. In univariate analysis, age, vital signs and consciousness on admission, history of liver cirrhosis, onset with hematemesis, admission hemoglobin, varicose veins bleeding, peptic ulcer bleeding, red blood cell infusion, tracheal intubation and the use of vasopressors after admission were risk factors for the 90-day mortality and rebleeding rate. Multivariate logistic regression analysis showed that patients with previous bleeding≥4 times had a higher risk of the 90-day mortality ( OR=2.17, 95% CI: 1.04-4.57, P=0.040) and rebleeding ( OR=2.32, 95% CI: 1.19-4.53, P=0.013). Conclusions:The history of previous bleeding≥ 4 times can be used as an independent risk factor for the 90-day mortality and rebleeding in patients with acute UGIB.