ObjectiveTo address the challenges of unstructured classical Chinese expressions， nested entity relationships， and limited annotated data in famous traditional Chinese medicine（TCM） case records， this study proposes a joint relation extraction framework that integrates data augmentation and entity mapping， aiming to support the construction of TCM diagnostic knowledge graphs and clinical pattern mining. MethodsWe developed an annotation structure for entities and their relationships in TCM case texts and applied a data augmentation strategy by incorporating multiple ancient texts to expand the relation extraction dataset. A cascade binary tagging framework for relation triple extraction（CasRel） model for TCM semantics was designed， integrating a pre-trained bidirectional encoder representations from transformers（BERT） layer for classical TCM texts to enhance semantic representation， and using a head entity-relation-tail entity mapping mechanism to address entity nesting and relation overlapping issues. ResultsExperimental results showed that the CasRel model， combining data augmentation and entity mapping， outperformed the pipeline-based Bert-Radical-Lexicon（BRL）-bidirectional long short-term memory（BiLSTM）-Attention model. The overall precision， recall， and F₁-score across 12 relation types reached 65.73%， 64.03%， and 64.87%， which represent improvements of 14.26%， 7.98%， and 11.21% compared to the BRL-BiLSTM-Attention model， respectively. Notably， the F₁-score for tongue syndrome relations increased by 22.68%（69.32%）， and the prescription-syndrome relations performed the best with the F₁-score of 70.10%. ConclusionThe proposed framework significantly improves the semantic representation and complex dependencies in TCM texts， offering a reusable technical framework for structured mining of TCM case records. The constructed knowledge graph can support clinical syndrome differentiation， prescription optimization， and drug compatibility， providing a methodological reference for TCM artificial intelligence research.

To explore the advantages of traditional Chinese medicine （TCM） and integrative TCM-Western medicine approaches in the treatment of diabetic microvascular complications （DMC）， refine key pathophysiological insights and treatment principles， and promote academic innovation and strategic research planning in the prevention and treatment of DMC. The 38th session of the Expert Salon on Diseases Responding Specifically to Traditional Chinese Medicine， hosted by the China Association of Chinese Medicine， was held in Beijing， 2024. Experts in TCM， Western medicine， and interdisciplinary fields convened to conduct a systematic discussion on the pathogenesis， diagnostic and treatment challenges， and mechanism research related to DMC， ultimately forming a consensus on key directions. Four major research recommendations were proposed. The first is addressing clinical bottlenecks in the prevention and control of DMC by optimizing TCM-based evidence evaluation systems. The second is refining TCM core pathogenesis across DMC stages and establishing corresponding "disease-pattern-time" framework. The third is innovating mechanism research strategies to facilitate a shift from holistic regulation to targeted intervention in TCM. The fourth is advancing interdisciplinary collaboration to enhance the role of TCM in new drug development， research prioritization， and guideline formulation. TCM and integrative approaches offer distinct advantages in managing DMC. With a focus on the diseases responding specifically to TCM， strengthening evidence-based support and mechanism interpretation and promoting the integration of clinical care and research innovation will provide strong momentum for the modernization of TCM and the advancement of national health strategies.

To investigate the mechanism of action of Syngnathus extract in treating knee osteoarthritis of rats, forty-eight male SD rats were randomly divided into the blank group, model group, positive drug group, as well as low-dose, medium-dose, and high-dose groups of Syngnathus extract. The rat model of knee osteoarthritis was constructed by intra-articular injection of sodium iodoacetate. After successful modeling, celecoxib(18 mg·kg~(-1)·d~(-1)) and Syngnathus extract(0.4, 0.8, and 1.6 g·kg~(-1)·d~(-1)) were given in different groups by gavage intervention for two weeks. Hematoxylin-eosin(HE) staining was used to observe the histopathological changes of cartilage in knee joints, and enzyme-linked immunosorbent assay(ELISA) was used to detect the expression level of inflammatory factors in serum. Real-time fluorescence quantitative PCR, Western blot, and immunohistochemistry were used to detect the levels of phosphatidylinositol 3-kinase(PI3K)/protein kinase B(Akt)/mammalian target protein of rapamycin(mTOR) pathway-related mRNA and protein expression. The results showed that, comparied with the blank group, the cartilage surface of the knee joints of rats in the model group was uneven, with disorganized levels and defective cartilage tissue. The serum levels of interleukin-1β(IL-1β), interleukin-6(IL-6), and tumor necrosis factor-α(TNF-α) and the mRNA levels of PI3K, Akt, and mTOR in cartilage tissue, as well as the protein expression levels of phosphorylated PI3K(p-PI3K)/PI3K, phosphorylated Akt(p-Akt)/Akt, phosphorylated mTOR(p-mTOR)/mTOR, and P62 were significantly increased. Beclin1 protein expression was decreased. Comparied with the model group, the number of chondrocytes in the knee joint of rats in each group of Syngnathus extract increased, and the arrangement of chondrocytes was relatively neat. The cartilage layer was restored, and the serum levels of IL-1β, IL-6, and TNF-α, as well as the mRNA expression levels of PI3K, Akt, and mTOR in cartilage tissue were significantly reduced. The protein expression levels of p-PI3K/PI3K, p-Akt/Akt, p-mTOR/mTOR, and P62 were significantly reduced in the rats in the middle-dose and high-dose groups of Syngnathus extract, and the Beclin1 protein expression was significantly increased. The protein expression levels of p-PI3K/PI3K, p-Akt/Akt, and P62 in rats in the low-dose group of Syngnathus extract were significantly reduced. In summary, Syngnathus extract may be used to treat knee osteoarthritis by inhibiting the expression of PI3K/Akt/mTOR signaling pathway, so as to alleviate the inflammatory response in the organism, enhance the autophagy activity of chondrocytes, and reduce the apoptosis of chondrocytes.
Animals ; TOR Serine-Threonine Kinases/genetics* ; Male ; Rats, Sprague-Dawley ; Signal Transduction/drug effects* ; Proto-Oncogene Proteins c-akt/genetics* ; Rats ; Osteoarthritis, Knee/metabolism* ; Drugs, Chinese Herbal/administration & dosage* ; Phosphatidylinositol 3-Kinases/genetics* ; Humans

The tumor microenvironment is a crucial factor in tumor occurrence and progression. The hypoxic microenvironment is widely present in tumor tissue and is a key endogenous factor accelerating tumor deterioration. The "blood stasis toxin" theory, as an emerging perspective in tumor research, is regarded as the unique "soil" in tumor progression from the perspective of traditional Chinese medicine(TCM) due to its dynamic evolution mechanism, which closely resembles the formation of the hypoxic microenvironment. Scientifically integrating TCM theories with the biological characteristics of tumors and exploring precise syndrome differentiation and treatment strategies are key to achieving comprehensive tumor prevention and control. This article focused on the hypoxic microenvironment of the tumor, elucidating its formation mechanisms and evolutionary processes and carefully analyzing the internal relationship between the "blood stasis toxin" theory and the hypoxic microenvironment. Additionally, it explored the interaction among blood stasis, toxic pathogens, and hypoxic environment and proposed micro-level prevention and treatment strategies targeting the hypoxic microenvironment based on the "blood stasis toxin" theory, aiming to provide TCM-based theoretical support and therapeutic approaches for precise regulation of the hypoxic microenvironment.
Humans ; Tumor Microenvironment/drug effects* ; Neoplasms/therapy* ; Animals ; Medicine, Chinese Traditional ; Disease Progression ; Drugs, Chinese Herbal

This study predicts the potential mechanism of Hippocampus in the treatment of knee osteoarthritis(KOA) through network pharmacology, with preliminary verification using molecular docking and animal experiments. The database was used to screen the active chemical components of Hippocampus and the targets of KOA, and Gene Ontology(GO) functional analysis, Kyoto Encyclopedia of Genes and Genomes(KEGG) pathway enrichment analysis, and molecular docking were performed on the relevant core targets to preliminarily explore the potential targets and mechanisms of Hippocampus in the treatment of KOA. A rat KOA model was constructed by intra-articular injection of sodium iodoacetate, and the rats were intervened with different doses of Hippocampus decoction and celecoxib. The expression of relevant targets was detected through hematoxylin-eosin(HE) staining, enzyme-linked immunosorbent assay(ELISA), RT-qPCR, and Western blot to further validate the network pharmacology results. A total of 23 drug-like components of the Hippocampus were screened, and 128 common targets with KOA were identified, involving interleukin-17(IL-17) signaling pathway, transcription factor(FoxO) signaling pathway, tumor necrosis factor(TNF) signaling pathway. Molecular docking results showed that the screened core chemical components exhibited good affinity with key targets. HE staining demonstrated that Hippocampus improved the morphology of the cartilage layer. ELISA confirmed that Hippocampus significantly reduced the levels of IL-6 and TNF-α in the serum of KOA rats. Western blot and RT-qPCR analysis showed that Hippocampus significantly reduced the expression of IL-6, TNF-α, matrix metalloproteinase(MMP) 13, IL-17A, nuclear factor κB activator 1(ACT1), tumor necrosis factor receptor-associated factor 6(TRAF6) and nuclear factor κB(NF-κB) in cartilage tissue. The results suggest that Hippocampus can alleviate the degree of joint damage in the KOA rat model induced by sodium iodoacetate. The mechanism of action is related to the inhibition of the IL-17 signaling pathway, reduction of inflammation, and inhibition of extracellular matrix(ECM) degradation.
Animals ; Molecular Docking Simulation ; Rats ; Drugs, Chinese Herbal/administration & dosage* ; Network Pharmacology ; Male ; Osteoarthritis, Knee/metabolism* ; Rats, Sprague-Dawley ; Signal Transduction/drug effects* ; Humans ; Interleukin-17/metabolism* ; Tumor Necrosis Factor-alpha/metabolism* ; Disease Models, Animal ; Hippocampus/chemistry*

Cardiotocography (CTG) is a non-invasive and important tool for diagnosing fetal distress during pregnancy. To meet the needs of intelligent fetal heart monitoring based on deep learning, this paper proposes a TWD-MOAL deep active learning algorithm based on the three-way decision (TWD) theory and multi-objective optimization Active Learning (MOAL). During the training process of a convolutional neural network (CNN) classification model, the algorithm incorporates the TWD theory to select high-confidence samples as pseudo-labeled samples in a fine-grained batch processing mode, meanwhile low-confidence samples annotated by obstetrics experts were also considered. The TWD-MOAL algorithm proposed in this paper was validated on a dataset of 16 355 prenatal CTG records collected by our group. Experimental results showed that the algorithm proposed in this paper achieved an accuracy of 80.63% using only 40% of the labeled samples, and in terms of various indicators, it performed better than the existing active learning algorithms under other frameworks. The study has shown that the intelligent fetal heart monitoring model based on TWD-MOAL proposed in this paper is reasonable and feasible. The algorithm significantly reduces the time and cost of labeling by obstetric experts and effectively solves the problem of data imbalance in CTG signal data in clinic, which is of great significance for assisting obstetrician in interpretations CTG signals and realizing intelligence fetal monitoring.
Humans ; Pregnancy ; Female ; Cardiotocography/methods* ; Deep Learning ; Neural Networks, Computer ; Algorithms ; Fetal Monitoring/methods* ; Heart Rate, Fetal ; Fetal Distress/diagnosis* ; Fetal Heart/physiology*

OBJECTIVES: To develop and validate a preoperative clinical-radiomics model for predicting overall survival (OS) and disease-free survival (DFS) in patients with extrahepatic cholangiocarcinoma (eCCA) undergoing radical resection. METHODS: In this retrospective study, consecutive patients with pathologically-confirmed eCCA who underwent radical resection at our institution from 2015 to 2022 were included. The patients were divided into a training cohort and a validation cohort according to the chronological order of their CT examinations. Least absolute shrinkage and selection operator (LASSO)-Cox regression was employed to select predictive radiomic features and clinical variables. The selected features and variables were incorporated into a Cox regression model. Model performance for 1-year OS and DFS prediction was assessed using calibration curves, area under receiver operating characteristic curve (AUC), and concordance index (C-index). RESULTS: This study included 123 patients (mean age 64.0 ± 8.4 years, 85 males/38 females), with 86 in the training cohort and 37 in the validation cohort. The OS-predicting model included four clinical variables and four radiomic features. It achieved a training cohort AUC of 0.858 (C-index = 0.800) and a validation cohort AUC of 0.649 (C-index = 0.605). The DFS-predicting model included four clinical variables and four other radiomic features. It achieved a training cohort AUC of 0.830 (C-index = 0.760) and a validation cohort AUC of 0.717 (C-index = 0.616). CONCLUSIONS The preoperative clinical-radiomics models show promise as a tool for predicting 1-year OS and DFS in eCCA patients after radical surgery.
Humans ; Male ; Female ; Retrospective Studies ; Middle Aged ; Cholangiocarcinoma/mortality* ; Prognosis ; Bile Duct Neoplasms/mortality* ; Tomography, X-Ray Computed/methods* ; Aged ; Radiomics

In-depth study of the components of polymyxins is the key to controlling the quality of this class of antibiotics. Similarities and variations of components present significant analytical challenges. A two-dimensional (2D) liquid chromatography-mass spectrometr (LC-MS) method was established for screening and comprehensive profiling of compositions of the antibiotic colistimethate sodium (CMS). A high concentration of phosphate buffer mobile phase was used in the first-dimensional LC system to get the components well separated. For efficient and high-accuracy screening of CMS, a targeted method based on a self-constructed high resolution (HR) mass spectrum database of CMS components was established. The database was built based on the commercial MassHunter Personal Compound Database and Library (PCDL) software and its accuracy of the compound matching result was verified with six known components before being applied to genuine sample screening. On this basis, the unknown peaks in the CMS chromatograms were deduced and assigned. The molecular formula, group composition, and origins of a total of 99 compounds, of which the combined area percentage accounted for more than 95% of CMS components, were deduced by this 2D-LC-MS method combined with the MassHunter PCDL. This profiling method was highly efficient and could distinguish hundreds of components within 3 h, providing reliable results for quality control of this kind of complex drugs.

Serine protease inhibitor Kazal-type (SPINK) is a skin keratinizing protease inhibitor, which was initially found in animal serum and is widely present in plants, animals, bacteria, and viruses, and they act as key regulators of skin keratinizing proteases and are involved in the regulation of keratinocyte proliferation and inflammation, primarily through the inhibition of deregulated tissue kinin-releasing enzymes (KLKs) in skin response. This process plays a crucial role in alleviating various skin problems caused by hyperkeratinization and inflammation, and can greatly improve the overall condition of the skin. Specifically, the different members of the SPINK family, such as SPINK5, SPINK6, SPINK7, and SPINK9, each have unique biological functions and mechanisms of action. The existence of these members demonstrates the diversity and complexity of skin health and disease. First, SPINK5 mutations are closely associated with the development of various skin diseases, such as Netherton’s syndrome and atopic dermatitis, and SPINK5 is able to inhibit the activation of the STAT3 signaling pathway, thereby effectively preventing the metastasis of melanoma cells, which is important in preventing the invasion and migration of malignant tumors. Secondly, SPINK6 is mainly distributed in the epidermis and contains lysine and glutamate residues, which can act as a substrate for epidermal transglutaminase to maintain the normal structure and function of the skin. In addition, SPINK6 can activate the intracellular ERK1/2 and AKT signaling pathways through the activation of epidermal growth factor receptor and protease receptor-2 (EphA2), which can promote the migration of melanoma cells, and SPINK6 further deepens its role in stimulating the migration of malignant tumor cells by inhibiting the activation of STAT3 signaling pathway. This process further deepens its potential impact in stimulating tumor invasive migration. Furthermore, SPINK7 plays a role in the pathology of some inflammatory skin diseases, and is likely to be an important factor contributing to the exacerbation of skin diseases by promoting aberrant proliferation of keratinocytes and local inflammatory responses. Finally, SPINK9 can induce cell migration and promote skin wound healing by activating purinergic receptor 2 (P2R) to induce phosphorylation of epidermal growth factor and further activating the downstream ERK1/2 signaling pathway. In addition, SPINK9 also plays an antimicrobial role, preventing the interference of some pathogenic microorganisms. Taken as a whole, some members of the SPINK family may be potential targets for the treatment of dermatological disorders by regulating multiple biological processes such as keratinization metabolism and immuno-inflammatory processes in the skin. The development of drugs such as small molecule inhibitors and monoclonal antibodies has great potential for the treatment of dermatologic diseases, and future research on SPINK will help to gain a deeper understanding of the physiopathologic processes of the skin. Through its functions and regulatory mechanisms, the formation and maintenance of the skin barrier and the occurrence and development of inflammatory responses can be better understood, which will provide novel ideas and methods for the prevention and treatment of skin diseases.

ObjectiveTo combine metabolomics， proteomics， and transcriptomics to analyze the biological characteristics of damp-heat toxin accumulation syndrome and damp-heat accumulation syndrome in acute gout. MethodsBlood samples were collected from 15 patients with damp-heat toxin accumulation syndrome and 15 patients with damp-heat accumulation syndrome in acute gout in clinical practice. Metabolomics technology was applied to detect serum metabolites， and an orthogonal partial sample least squares discriminant analysis model was constructed to screen for metabolites with significant intergroup changes， and enrichment pathway analysis and receiver operating characteristic （ROC） curve analysis were performed. Astral data independence acquisition （DIA） was used to detect serum proteins， perform principal component analysis and screen differential proteins， demonstrate differential ploidy by radargram， apply subcellular localisation to analyse protein sources， and finally apply weighted gene co-expression network analysis （WGCNA） to find key proteins. Transcriptome sequencing technology was also applied to detect whole blood mRNA， screen differential genes and perform WGCNA， and construct machine learning models to screen key genes. ResultsMetabolome differential analysis revealed 62 differential metabolites in positive ion mode and 26 in negative ion mode. These differential metabolites were mainly enriched in the mTOR signaling pathway and FoxO signaling pathway， with trans-3,5-dimethoxy-4-hydroxycinnamaldehyde， guanabenz， 4-aminophenyl-1-thio-beta-d-galactopyranoside showing the highest diagnostic efficacy. The proteome differential analysis found that 55 proteins up-regulated and 20 proteins down-regulated in the samples of damp-heat toxin accumulation syndrome. Notably， myelin basic protein （MBP）， transferrin （TF）， DKFZp686N02209， and apolipoprotein B （APOB） showed the most significant differences in expression. Differential proteins were mainly enriched in pathways related to fat digestion and absorption， lipid and atherosclerosis， and cholesterol metabolism. WGCNA showed the highest correlation between damp-heat toxin accumulation syndrome and the brown module， with proteins in this module primarily enriched in the hypoxia-inducible factor 1 （HIF-1） signaling pathway and lipid and atherosclerosis. Transcriptomic differential analysis identified 252 differentially expressed genes， with WGCNA indicating the highest correlation between damp-heat toxin accumulation syndrome and the midnight blue module. The random forest （RF） model was identified as the optimal machine learning model， predicting apolipoprotein B receptor （APOBR）， far upstream element-binding protein 2 （KHSRP）， POU domain class 2 transcription factor 2 （POU2F2）， EH domain-containing protein 1 （EHD1）， and family with sequence similarity 110A （FAM110A） as key genes. Integrated multi-omics analysis suggested that damp-heat toxin accumulation syndrome in the acute phase of gout is closely associated with lipid metabolism， particularly APOB. ConclusionCompared to damp-heat accumulation syndrome in the acute phase of gout， damp-heat toxin accumulation syndrome is more closely associated with lipid metabolism， particularly APOB， and lipid metabolism disorders contribute to the development of damp-heat toxin accumulation syndrome in patients with acute gout.