Objective: To systematically characterize the developmental trajectory and interdisciplinary integration of intelligent diagnosis in traditional Chinese medicine (TCM) through quantitative topic evolution analysis, we addressed the fragmentation of existing research and clarified the long-term research structure and evolutionary patterns of the field. Methods: A topic evolution analysis was performed on Chinese-language literature pertaining to intelligent diagnosis in TCM. Publications were retrieved from the China National Knowledge Infrastructure (CNKI), Wanfang Data, and China Science and Technology Journal Database (VIP), covering the period from database inception to July 3, 2025. A hybrid segmentation approach, based on cumulative publication growth trends and inflection point detection, was applied to divide the research timeline into distinct stages. Subsequently, the latent Dirichlet allocation (LDA) model was used to extract research topics, followed by alignment and evolutionary analysis of topics across different stages. Results: A total of 3 919 publications published between 2003 and 2025 were included, and the research trajectory was divided into five stages based on data-driven breakpoint detection. The field exhibited a clear evolutionary shift from early rule-based systems and tongue-pulse image and signal analysis (2006 – 2010), to machine-learning-based syndrome and prescription modeling (2011 – 2015), followed by deep-learning-driven pattern recognition and formula association (2016 – 2020). Since 2021, research has increasingly emphasized knowledge-graph construction, multimodal integration, and intelligent clinical decision-support systems, with recent studies (2024 – 2025) showing the emergence of large language models and agent-based diagnostic frameworks. Topic evolution analysis further revealed sustained cross-stage continuity in syndrome modeling and prescription association analysis, alongside the progressive consolidation of integrated intelligent diagnostic platforms. Conclusion By identifying key technological transitions and persistent core research themes, our findings offer a structured reference framework for the design of intelligent diagnostic systems, the construction of knowledge-driven clinical decision-support tools, and the alignment of AI models with TCM diagnostic logic. Importantly, the stage-based evolutionary insights derived from this analysis can inform future methodological choices, improve model interpretability and clinical applicability, and support the translation of intelligent TCM diagnosis from experimental research to real-world clinical practice.

Chronic post-surgical pain (CPSP) is a common long-term complication following lung surgery. Its high incidence significantly impacts patients’ quality of life and functional recovery, and imposes a substantial socioeconomic burden. This consensus aims to systematically establish a standardized integrated Chinese and Western medicine diagnostic and treatment framework for chronic post-lung surgery pain (CPLSP). Based on the latest domestic and international evidence-based medical research and multidisciplinary clinical experience, the working group comprehensively elaborates on core issues regarding CPLSP, including its definition, epidemiology, pathogenesis, clinical assessment, Western medical treatment, traditional Chinese medicine (TCM) treatment, and integrated strategies. The consensus emphasizes a patient-centered approach, adhering to the principles of multimodality, individualization, and stepwise management, highlighting the synergistic advantages of integrating Chinese and Western medicine throughout the entire perioperative management cycle encompassing "perioperative anti-inflammation, acute analgesia, and chronic rehabilitation." Through systematic literature retrieval and evidence integration, a total of 9 core recommendations were established to provide scientifically sound and clinically practical guidance.

To investigate the risk factors for acute kidney injury (AKI) following the use of amphotericin B deoxycholate and to develop a predictive model to guide clinical monitoring and intervention.

ObjectiveBased on 16S rDNA technology and molecular biology methods， the molecular mechanism of Shenling Baizhusan in the treatment of diarrhea-predominant irritable bowel syndrome （IBS-D） was investigated. MethodsThe 42 SD rats with SPF were randomly divided into no control group， SLBZS-H， medium （SLBZS-M）， low （SLBZS-L） dose group， positive control group and model group， with 7 rats in each group. The rat model of IBS-D was prepared by ice-cold senna （0.45 g∙mL^-1） gavage （10 mL∙kg^-1） combined with restraint stress for 14 consecutive days. After successful modeling， the corresponding drugs were given to each group with a gavage volume of 10 mL∙kg^-1： The positive group was administered with 2.36 ， 1.18， 0.59 g∙mL^-1 of Shenling Baizhusan in the Positive group and the Model group with the same volume of normal saline for 14 d. The general condition of the rats： Weight， feces， mental state and death were observed and recorded. The body weight， abdominal wall retraction reflex score （AWR） and loose stool rate of rats in each group were measured before （the first day）， after the model （day 14） and after treatment （day 28）. Hematoxylin-eosin staining was used to observe the morphological characteristics of colon tissues of experimental animals. Enzyme-linked immunosorbent assay was used to quantitatively analyze the concentration of inflammatory mediators in the peripheral blood of experimental animals. Western blotting was used to detect the expression levels of key proteins of Toll-like receptor 4 （TLR4）， Toll-like receptor 2 （TLR2）， myeloid differentiation factor 88 （MyD88） and nuclear factor-κB （NF-κB） signaling pathway in rat colon tissue. 16S rDNA technology was used to detect the structural changes of intestinal microbiota in rats. ResultsCompared with Control， the colon of the Model group showed partial mucosal epithelial shedding and inflammatory cell infiltration. The contents of TNF-α， IL-1β， IL-6 and 5-HT in serum increased （P<0.05）， the protein expressions of TLR2， TLR4， MyD88 and NF-κB in colon tissue increased （P<0.05）， the diversity indices of Richness， Chao1， abundance-based coverage estimator（ACE） and Shannon decreased （P<0.05）， and the phylum Firmicutes， Actinobacteria， The relative richness of Bacteroides-H， Lactobacillus and Ligilactobacillus decreased （P<0.05）， while the relative richness of Bacteroidetes， Proteobacteria and Prevotella increased （P<0.05）. Compared with the model group， the colonic structure and organization of the SLBZS-H group， SLBZS-M group， SLBZS-L group and Positive group were clearer， and only a small number of inflammatory cells were present in some areas， and the serum contents of TNF-α， IL-1β， IL-6 and 5-HT were decreased （P<0.05）， TLR2， TLR4， The protein expressions of MyD88 and NF-κB decreased （P<0.05）， and compared with the model group， the diversity indices of Richness， Chao1， ACE and Shannon in the SLBZS-H， SLBZS-M and SLBZS-L groups increased （P<0.05）， and the richness of Firmicutes and Actinobacteria increased （P<0.05）. The richness of Proteobacteria and Prevotella decreased （P<0.05）， and the abundance of Prevotella decreased （P<0.05）， Bacteroides-H， Muribaculum， Lactobacillus and salivarius in the Positive group salivarius （P<0.05）. ConclusionShenling Baizhusan can effectively treat IBS-D， and its molecular mechanism may be to play a therapeutic role by improving intestinal flora and inhibiting the TLRS/MyD88/NF-κB signaling pathway to reduce inflammatory response.

This paper outlines the development of artificial intelligence （AI） and its applications in traditional Chinese medicine （TCM） research， and elucidates the roles and advantages of large language models， knowledge graphs， and natural language processing in advancing syndrome identification， prescription generation， and mechanism exploration. Using spleen-stomach diseases as an example， it demonstrates the empowering effects of AI in classical literature mining， precise clinical syndrome differentiation， efficacy and safety prediction， and intelligent education， highlighting an upgraded research paradigm that evolves from data-driven and knowledge-driven approaches to intelligence-driven models. To address challenges related to privacy protection and regulatory compliance in cross-institutional data collaboration， a "trusted federated evidence-based analysis platform for TCM spleen-stomach diseases" is proposed， integrating blockchain-based smart contracts， federated learning， and secure multi-party computation. The deep integration of AI with privacy-preserving computing is reshaping research and clinical practice in TCM spleen-stomach diseases， providing feasible pathways and a technical framework for building a high-quality， trustworthy TCM big-data ecosystem and achieving precision syndrome differentiation.

This study explored the prescription pattern of traditional Chinese medicine(TCM) in the treatment of hypertensive left ventricular hypertrophy(LVH), so as to provide a relevant theoretical basis for the clinical diagnosis and treatment of hypertensive LVH. The study systematically searched the databases of CNKI, Wanfang, VIP, and SinoMed to screen out the qualified literature on TCM treatment of hypertensive LVH and used Microsoft Excel 2021 to establish the relevant prescription database. It also counted the frequency, property, flavor, and meridian affiliation of TCM in the prescriptions and classified their efficacy. The study used Lantern 5.0 and Rstudio software to analyze the hidden structural models and association rules of the high-frequency TCM with a frequency of >3.50% and adopted Origin 2024 software to visualize the data, so as to explore the prescription pattern of TCM in treating hypertensive LVH. The results showed that a total of 128 TCM prescriptions were included, involving 163 TCM with a total frequency of 1 242. The high-frequency TCM included Salviae Miltiorrhizae Radix et Rhizoma, Uncariae Ramulus Cum Uncis, Gastrodiae Rhizoma, Poria, and Chuanxiong Rhizoma, with the main efficacy from blood-activating and stasis-resolving herbs, tonic herbs, and liver-calming and wind-extinguishing herbs. The latent structure analysis(LSA) identified 10 latent variables, 20 latent classes, 7 comprehensive clustering models, and 23 core prescriptions. It was speculated that the common syndromes of hypertensive LVH included blood stasis obstructing the collaterals, ascending hyperactivity of liver Yang, Yin deficiency with Yang hyperactivity, and intermingled phlegm and blood stasis. The association rule analysis yielded 33 strong association rules, with the highest comprehensive association rule being Gastrodiae Rhizoma→Uncariae Ramulus Cum Uncis. Hypertensive LVH is characterized by asthenia in origin and asthenia in superficiality, with Yin deficiency and Qi deficiency as the origin and blood stasis and phlegm as the superficiality. Clinical treatment focuses on activating blood circulation, resolving stasis, tonifying Qi, and nourishing Yin, combined with syndrome-specific therapies such as calming wind and stopping convulsions, clearing heat, eliminating dampness and resolving phlegm, and promoting diuresis and reducing swelling.
Drugs, Chinese Herbal/therapeutic use* ; Data Mining ; Humans ; Hypertension/complications* ; Hypertrophy, Left Ventricular/physiopathology* ; Medicine, Chinese Traditional ; Drug Prescriptions

This study aimed to characterize and identify the non-volatile components in aqueous and ethanolic extracts of the stems and leaves of Rhododendron tomentosum by using sensitive and efficient ultra-performance liquid chromatography-quadrupole-time of flight mass spectrometry(UHPLC-Q-TOF-MS) combined with a self-built information database. By comparing with reference compounds, analyzing fragment ion information, searching relevant literature, and using a self-built information database, 118 compounds were identified from the aqueous and ethanolic extracts of R. tomentosum, including 35 flavonoid glycosides, 15 phenolic glycosides, 12 flavonoids, 7 phenolic acids, 7 phenylethanol glycosides, 6 tannins, 6 phospholipids, 5 coumarins, 5 monoterpene glycosides, 6 triterpenes, 3 fatty acids, and 11 other types of compounds. Among them, 102 compounds were reported in R. tomentosum for the first time, and 36 compounds were identified by comparing them with reference compounds. The chemical components in the ethanolic and aqueous extracts of R. tomentosum leaves and stems showed slight differences, with 84 common chemical components accounting for 71.2% of the total 118 compounds. This study systematically characterized and identified the non-volatile chemical components in the ethanolic and aqueous extracts of R. tomentosum for the first time. The findings provide a reference for active ingredient research, quality control, and product development of R. tomentosum.
Rhododendron/chemistry* ; Chromatography, High Pressure Liquid/methods* ; Drugs, Chinese Herbal/chemistry* ; Mass Spectrometry/methods* ; Plant Leaves/chemistry*

The quality of drugs is a crucial premise for ensuring the safety and effectiveness of clinical medication, while quality control during the pharmaceutical process directly affects the quality and consistency of the final product formulation. However, there is a lack of a comprehensive and scientific system for assessing and optimizing the quality control level during the manufacturing process in the field of drug quality control. Therefore, this study proposed the concept of "pharmaceutical process omics", clarified its advantages in guiding drug production, and explored in depth the research approaches, diverse analytical techniques, and broad range of applications in drug quality control. In addition, this study anticipated the broad application prospects of pharmaceutical process omics in the field of drug quality control, aiming to provide a scientific basis for the development of pharmaceutical process quality control standards.
Quality Control ; Humans ; Drugs, Chinese Herbal/chemistry*

OBJECTIVE: To explore the effectiveness of posterior single-level osteotomy with 360° release and correction for the treatment of osteoporotic vertebral compression fractures (OVCF) complicated with moderate to severe kyphosis. METHODS: A retrospective analysis was conducted on 11 patients with OVCF complicated with moderate to severe kyphosis between January 2022 and March 2023. There were 4 males and 7 females with an average age of 57 years ranging from 47 to 69 years. The disease duration ranged from 3 to 15 months, with an average of 7 months. Fracture segments included T ₁₁ in 3 cases, T ₁₂ in 5, L ₁ in 2, and L ₂ in 1. The T value of lumbar spine bone density was -5.0 to -2.0, with an average of -3.5. The preoperative neurological function was grade E according to Frankel grading. The Pfirrmann classification of the intervertebral disc above the injured vertebra was grade Ⅲ in 8 cases and grade Ⅳ in 3 cases. All patients underwent posterior single-level osteotomy with 360° release and correction. The operation time, intraoperative blood loss, hospital stay, and postoperative complications were recorded. Thoracolumbar local kyphosis Cobb angle, the mean height of the functional spinal unit (FSU), the sagittal vertical axis (SVA), and the sagittal index (SI) were measured. The visual analogue scale (VAS) score and Oswestry disability index (ODI) were used to evaluate the improvement of pain and function before operation, at 1 month after operation, and at last follow-up. RESULTS: The operation successfully completed in all patients, and there was no obvious complication. The operation time ranged from 100 to 190 minutes, with an average of 153 minutes, and the intraoperative blood loss ranged from 200 to 800 mL, with an average of 468 mL. The length of hospital stay was 8-14 days (mean, 12 days). All patients were followed up 6-24 months, with an average of 12.4 months. At last follow-up, all the 11 patients had bony fusion in the osteotomy area, and there was no displacement or subsidence of the Cage, no complication such as internal fixation failure or pseudarthrosis formation was found. The Cobb angle of local thoracolumbar kyphosis, the mean height of FSU, SVA, and SI significantly improved immediately after operation and at last follow-up when compared with preoperative ones, and the VAS score and ODI also significantly improved at 1 month after operation and at last follow-up ( P<0.05); there was no significant difference in above indexes between the two time points after operation ( P>0.05). CONCLUSION Posterior single-level osteotomy with 360° release and correction is an effective surgical method for treating OVCF complicated with moderate to severe kyphosis, with definite early effectiveness.
Humans ; Kyphosis/etiology* ; Male ; Female ; Osteotomy/methods* ; Middle Aged ; Retrospective Studies ; Aged ; Spinal Fractures/diagnostic imaging* ; Fractures, Compression/diagnostic imaging* ; Osteoporotic Fractures/complications* ; Treatment Outcome ; Lumbar Vertebrae/injuries* ; Thoracic Vertebrae/injuries* ; Operative Time ; Fracture Fixation, Internal/methods*

Testicular histology based on testicular biopsy is an important factor for determining appropriate testicular sperm extraction surgery and predicting sperm retrieval outcomes in patients with azoospermia. Therefore, we developed a deep learning (DL) model to establish the associations between testicular grayscale ultrasound images and testicular histology. We retrospectively included two-dimensional testicular grayscale ultrasound from patients with azoospermia (353 men with 4357 images between July 2017 and December 2021 in The First Affiliated Hospital of Sun Yat-sen University, Guangzhou, China) to develop a DL model. We obtained testicular histology during conventional testicular sperm extraction. Our DL model was trained based on ultrasound images or fusion data (ultrasound images fused with the corresponding testicular volume) to distinguish spermatozoa presence in pathology (SPP) and spermatozoa absence in pathology (SAP) and to classify maturation arrest (MA) and Sertoli cell-only syndrome (SCOS) in patients with SAP. Areas under the receiver operating characteristic curve (AUCs), accuracy, sensitivity, and specificity were used to analyze model performance. DL based on images achieved an AUC of 0.922 (95% confidence interval [CI]: 0.908-0.935), a sensitivity of 80.9%, a specificity of 84.6%, and an accuracy of 83.5% in predicting SPP (including normal spermatogenesis and hypospermatogenesis) and SAP (including MA and SCOS). In the identification of SCOS and MA, DL on fusion data yielded better diagnostic performance with an AUC of 0.979 (95% CI: 0.969-0.989), a sensitivity of 89.7%, a specificity of 97.1%, and an accuracy of 92.1%. Our study provides a noninvasive method to predict testicular histology for patients with azoospermia, which would avoid unnecessary testicular biopsy.
Humans ; Male ; Azoospermia/diagnostic imaging* ; Deep Learning ; Testis/pathology* ; Retrospective Studies ; Adult ; Ultrasonography/methods* ; Sperm Retrieval ; Sertoli Cell-Only Syndrome/diagnostic imaging*