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.

OBJECTIVE To investigate the mechanism by which Qiaobai cold compress solution （QBCS） improves acne vulgaris （AV） based on transcriptomics and animal experiments. METHODS Rats were randomly divided into a blank control group （ n ＝6） and a modeling group （ n ＝30）. AV models were established in the modeling group by topical application of oleic acid to the inner surface of both ears， combined with subcutaneous injection of Cutibacterium acnes suspension into the auricle. Successfully modeled rats were further divided into the model group， positive control group （Tretinoin cream， 0.045 g/kg）， and QBCS low-， medium-， high-dose groups [3.55， 7.11， 14.22 g/kg （calculated by the amount of crude drug） ] ， with 6 rats in each group. Rats in each d rug group were treated with the corresponding drugs once daily for 14 consecutive days. After the final administration， changes in the appearance of the ears and histopathological changes in the ear tissues were observed， and serum levels of inflammatory factors， including tumor necrosis factor-α （TNF-α）， interleukin-6 （IL-6） and IL-1β， were measured. Auricular tissues from the blank control group， model group and QBCS medium-dose group were collected for transcriptome sequencing. Differential expressed genes （DEGs） were screened and subjected to Kyoto Encyclopedia of Genes and Genomes pathway enrichment analysis， followed by validation using real-time quantitative polymerase chain reaction and Western blot assay. RESULTS Compared with the model group， rats in all QBCS groups showed alleviated auricular acne symptoms， with reduced epidermal thickening， sebaceous gland hyperplasia， and inflammatory cell infiltration. Serum levels of TNF-α （except for the QBCS low-dose group）， IL-6 （except for the QBCS low-dose group） and IL-1β were significantly decreased （ P ＜0.05）. A total of 590 DEGs were identified （blank control group vs. model group）， and 596 DEGs were identified （model group vs. QBCS medium-dose group）. Above DEGs （blank control group vs. model group） were mainly enriched in Toll-like receptor （TLR） and nuclear factor-kappa B （NF-κB） signaling pathways， etc. Validation experiments showed that， compared with model group， low-， medium- and high-dose of QBCS reduced， to varying degrees， the mRNA expression of TNF-α， TLR2， interferon-γ and CXC chemokine ligand 8 in the auricular tissues of AV rats， increased the mRNA expression of peroxisome-proliferator-activated receptor gamma and tumor protein 53， and inhibited the phosphorylation of NF-κB p65 protein as well as the expressions of TLR2 and myeloid differentiation primary response protein 88（MyD88） （ P ＜0.05）. CONCLUSIONS QBCS can alleviate auricular inflammation and skin lesions in AV rats. This effect may be related to inhibition of the TLR/MyD88/NF-κB signaling pathway， thereby suppressing the expression of downstream inflammatory factors such as TNF-α.

Olfactory receptors (ORs) form the largest superfamily of G protein-coupled receptors (GPCRs). Traditionally recognized for their role in the nasal olfactory epithelium, where they mediate the sense of smell, accumulating evidence has firmly established their ectopic expression in non-olfactory tissues, including the intestine, lungs, and kidneys. The intestine, as the primary site for nutrient digestion and absorption, harbors a highly complex chemical environment. To adapt to this environment, the gut employs a sophisticated network of “chemosensors” to monitor luminal contents and maintain homeostasis. Among these sensors, intestinal ORs have emerged as crucial functional components, serving as a molecular bridge that connects environmental chemical signals—such as food-derived odorants—to specific physiological responses. This discovery has significantly deepened our understanding of how dietary flavors and compounds influence intestinal physiology at the molecular level. This review systematically summarizes the expression profiles, ligand classification, and biological functions of ORs within the gastrointestinal tract. Studies indicate that intestinal ORs exhibit distinct spatial distribution patterns across different gut segments and display cell-type specificity, particularly within enterocytes and enteroendocrine cells. These receptors function as versatile sensors capable of recognizing a wide variety of ligands, including exogenous dietary components, gut microbiota metabolites such as short-chain fatty acids, and endogenous small molecules like azelaic acid. Upon activation by specific ligands, intestinal ORs trigger intracellular signaling cascades, primarily involving the AC-cAMP-PKA pathway or calcium influx channels. A major focus of this review is to elucidate the molecular mechanisms by which these receptors regulate the secretion of gut hormones. Activation of specific ORs in enteroendocrine cells has been shown to stimulate the release of hormones such as glucagon-like peptide-1 (GLP-1), peptide YY (PYY), and serotonin (5-HT), thereby modulating systemic energy metabolism, glucose homeostasis, and gastrointestinal motility. Furthermore, the review addresses the critical roles of ORs in immune regulation and pathology. Evidence suggests that specific ORs contribute to the maintenance of intestinal immune homeostasis and may offer protection against inflammation. Beyond their involvement in inflammatory responses, ORs such as Olfr78 have been shown to regulate the differentiation and function of intestinal endocrine cells. Similarly, Olfr544 has been demonstrated to alleviate intestinal inflammation by remodeling the gut microbiome and metabolome. These findings collectively suggest that specific ORs hold promise as therapeutic targets for mitigating intestinal inflammation and maintaining gut homeostasis. Additionally, the review explores the emerging role of ORs in cancer. Although OR expression is often downregulated in tumor tissues compared to normal mucosa, activation of specific ORs by certain ligands can inhibit tumor cell proliferation and migration and induce apoptosis via pathways such as MEK/ERK and p38 MAPK. Conversely, other receptors, such as OR7C1, may serve as biomarkers for cancer-initiating cells. In conclusion, intestinal ORs represent a vital component of the gut’s sensory network. The review also discusses the translational potential of these findings. By elucidating the precise pairing relationships between dietary components and specific ORs, novel therapeutic strategies could be developed. Intestinal ORs may thus emerge as promising targets for nutritional and pharmacological interventions in metabolic diseases, inflammatory bowel diseases, and malignancies.

ObjectiveType I interferon (IFN-I) signaling is essential for antiviral innate immunity, yet its sustained or excessive activation contributes to the pathogenesis of several autoimmune diseases and interferonopathies, such as systemic lupus erythematosus and Aicardi-Goutières syndrome. Current strategies targeting this pathway, exemplified by JAK inhibitors, act mainly on downstream signal transduction and provide limited direct control over upstream IFN-I production, while also carrying the risk of broad immunosuppression. Phyllanthus emblica L. has long been used in traditional medicine for inflammatory disorders, but the bioactive constituent responsible for its regulation of IFN-I signaling and the underlying molecular mechanism have not been clearly defined. This study aimed to identify the active anti-inflammatory component of P. emblica and to characterize its mechanism of action on the IFN-I pathway in macrophages. MethodsActive components ofP. emblica and their candidate targets were screened by network pharmacology using the TCMSP and DrugBank databases (oral bioavailability≥30%, drug-likeness≥0.18) and intersected with inflammation-related genes retrieved from public databases. The predicted interaction between EGCG and IFN-I pathway proteins (TBK1, IRF3, STAT1) was evaluated by molecular docking, with BX795 and GSK8612 used as reference TBK1 inhibitors. Mechanistic experiments were performed in THP-1-derived macrophages and primary bone marrow-derived macrophages (BMDM). Upstream signaling was activated by transfection of the nucleic acid analogs poly(I∶C) and poly(dA∶dT) or by lipopolysaccharide (LPS) stimulation, whereas downstream signaling was activated by exogenous IFN-β. An siRNA-mediated TREX1 knockdown model was used to mimic endogenous nucleic acid-driven interferonopathy. Expression of IFN-β1 and interferon-stimulated genes (ISGs) was measured by RT-qPCR, protein phosphorylation by Western blot, and IFN-β secretion by ELISA. Cellular thermal shift assay (CETSA) and drug affinity responsive target stability (DARTS) were used to probe the interactionbetween EGCG and IRF3. ResultsNetwork pharmacology identified (-)-epigallocatechin-3-gallate (EGCG) as a candidate IFN-I-suppressive constituent of P. emblica, with predicted binding to TBK1, IRF3, and STAT1. Molecular docking yielded binding energies of -9.2, -7.2, and -8.2 kcal/mol for TBK1, IRF3, and STAT1, respectively, indicating an affinity for TBK1 comparable to that of the reference inhibitors BX795 (-5.7 kcal/mol) and GSK8612 (-6.4 kcal/mol). EGCG suppressed IFN-β1 and ISG mRNA expression under poly (I∶C), poly (dA∶dT), and LPS stimulation in both THP-1 macrophages and BMDM. At the protein level, EGCG reduced the phosphorylation of TBK1 and IRF3 without affecting the levels of the upstream sensors cGAS and RIG-I, and lowered IFN-β secretion in a concentration-dependent manner. CETSA and DARTS showed that EGCG did not enhance the thermal stability or protease resistance of IRF3, indicating that its effect on IRF3 is indirect. Following IFN-β stimulation, prolonged EGCG treatment reduced STAT1 phosphorylation in a time-dependent manner without an apparent change in IRF9, and partially attenuated ISG transcription; this effect was not monotonicly concentration-dependent, and CXCL10 showed the most consistent suppression. In TREX1-knockdown cells, the elevated mRNA levels of ISG15, ISG56, and CXCL10 were reduced by EGCG. ConclusionEGCG suppresses IFN-I responses by concurrently inhibiting TBK1-IRF3-dependent IFN‑β production and JAK-STAT1-mediated downstream transcription. These in vitro findings provide a mechanistic basis for the anti-inflammatory use of P. emblica in traditional medicine and identify EGCG as a candidate for further evaluation in interferon-driven autoimmune disease models.

Objective Sanguisorba officinalis is the principal medicinal ingredient of Sicaokeyin gel. Gallic acid is commonly used as a key indicator component for evaluating the quality of Sanguisorba officinalis and its preparations. To establish a HPLC method for the determinant of gallic acid in Sicaokeyin gel. Methods With gallic acid as reference substance，HPLC analysis was performed on a Agilent Eclipse XDB-C₁₈ column （4.6 mm ×25 mm，5 μm） with methanol-0.05%phosphoric acid （5∶95） under isocratic elution. The flow rate was 1.0 ml/min and the detection wavelength was 272 nm. The column temperature was 30℃, the injection volume was 10 μl. Results Gallic acid showed good linear relationship in the range of 1.004-50.18 μg/ml （r=0.999 9）. The average recovery was 102.9% （n=9）. Conclusion The method was easy to operate; the result was accurate and reliable, which could be used for the quality control of sanguisorba officinalis in Sicaokeyin gel.

AIM: To investigate the differences in ocular parameters among patients with varying degrees of myopia, analyze the correlation between tessellated fundus(FT)severity and ocular biometric parameters as well as fundus lesions, and evaluate the clinical value of peripheral retinal lesions, FT, and ultra-wide-field imaging(UWFI)in the risk assessment of myopic fundus lesions.METHODS: Patients with ametropia who were admitted to the Department of Ophthalmology, Liuzhou Red Cross Hospital from June 2022 to June 2025 were retrospectively collected.The participants were divided into four groups according to different spherical equivalent(SE): emmetropia and mild myopia group(-3.0 D

ObjectiveTraditional Chinese medicine (TCM) constitutes a valuable cultural heritage and an important source of antitumor compounds. Poria (Poria cocos (Schw.) Wolf), the dried sclerotium of a polyporaceae fungus, was first documented in Shennong’s Classic of Materia Medica and has been used therapeutically and dietarily in China for millennia. Traditionally recognized for its diuretic, spleen-tonifying, and sedative properties, modern pharmacological studies confirm that Poria exhibits antioxidant, anti-inflammatory, antibacterial, and antitumor activities. Pachymic acid (PA; a triterpenoid with the chemical structure 3β-acetyloxy-16α-hydroxy-lanosta-8,24(31)-dien-21-oic acid), isolated from Poria, is a principal bioactive constituent. Emerging evidence indicates PA exerts antitumor effects through multiple mechanisms, though these remain incompletely characterized. Neuroblastoma (NB), a highly malignant pediatric extracranial solid tumor accounting for 15% of childhood cancer deaths, urgently requires safer therapeutics due to the limitations of current treatments. Although PA shows multi-mechanistic antitumor potential, its efficacy against NB remains uncharacterized. This study systematically investigated the potential molecular targets and mechanisms underlying the anti-NB effects of PA by integrating network pharmacology-based target prediction with experimental validation of multi-target interactions through molecular docking, dynamic simulations, and in vitro assays, aimed to establish a novel perspective on PA’s antitumor activity and explore its potential clinical implications for NB treatment by integrating computational predictions with biological assays. MethodsThis study employed network pharmacology to identify potential targets of PA in NB, followed by validation using molecular docking, molecular dynamics (MD) simulations, MM/PBSA free energy analysis, RT-qPCR and Western blot experiments. Network pharmacology analysis included target screening via TCMSP, GeneCards, DisGeNET, SwissTargetPrediction, SuperPred, and PharmMapper. Subsequently, potential targets were predicted by intersecting the results from these databases via Venn analysis. Following target prediction, topological analysis was performed to identify key targets using Cytoscape software. Molecular docking was conducted using AutoDock Vina, with the binding pocket defined based on crystal structures. MD simulations were performed for 100 ns using GROMACS, and RMSD, RMSF, SASA, and hydrogen bonding dynamics were analyzed. MM/PBSA calculations were carried out to estimate the binding free energy of each protein-ligand complex. In vitro validation included RT-qPCR and Western blot, with GAPDH used as an internal control. ResultsThe CCK-8 assay demonstrated a concentration-dependent inhibitory effect of PA on NB cell viability. GO analysis suggested that the anti-NB activity of PA might involve cellular response to chemical stress, vesicle lumen, and protein tyrosine kinase activity. KEGG pathway enrichment analysis suggested that the anti-NB activity of PA might involve the PI3K/AKT, MAPK, and Ras signaling pathways. Molecular docking and MD simulations revealed stable binding interactions between PA and the core target proteins AKT1, EGFR, SRC, and HSP90AA1. RT-qPCR and Western blot analyses further confirmed that PA treatment significantly decreased the mRNA and protein expression of AKT1, EGFR, and SRC while increasing the HSP90AA1 mRNA and protein levels. ConclusionIt was suggested that PA may exert its anti-NB effects by inhibiting AKT1, EGFR, and SRC expression, potentially modulating the PI3K/AKT signaling pathway. These findings provide crucial evidence supporting PA’s development as a therapeutic candidate for NB.

Objective To introduce a modified technique of right ventricular outflow tract (RVOT) reconstruction using a handmade bicuspid pulmonary valve crafted from expanded polytetrafluoroethylene (ePTFE) and to summarize the early single-center experience. Methods Patients with complex congenital heart diseases (CHD) who underwent RVOT reconstruction with a handmade ePTFE bicuspid pulmonary valve due to pulmonary regurgitation at Guangdong Provincial People’s Hospital from April 2021 to February 2022 were selected. Postoperative artificial valve function and right heart function indicators were evaluated. Results A total of 17 patients were included, comprising 10 males and 7 females, with a mean age of (18.18±12.14) years and a mean body weight of (40.94±19.45) kg. Sixteen patients underwent reconstruction with a handmade valved conduit, with conduit sizes ranging from 18 to 24 mm. No patients required mechanical circulatory support, and no in-hospital deaths occurred. During a mean follow-up period of 12.89 months, only one patient developed valve dysfunction, and no related complications or adverse events were observed. The degree of pulmonary regurgitation was significantly improved post-RVOT reconstruction and during follow-up compared to preoperative levels (P<0.001). Postoperative right atrial diameter, right ventricular diameter, and tricuspid regurgitation area were all significantly reduced compared to preoperative values (P<0.05). Conclusion The use of a 0.1 mm ePTFE handmade bicuspid pulmonary valve for RVOT reconstruction in complex CHD is a feasible, effective, and safe technique.

ObjectiveTo analyze the epidemiological trends and characteristics of brucellosis in humans (hereinafter referred to as brucellosis) in Tangshan City, Hebei Province from 2016 to 2023, and to provide a scientific basis for formulating brucellosis prevention and control strategies in the region. MethodsThe incidence data of human brucellosis in Tangshan City from 2016 to 2023 were collected from the China Disease Prevention and Control Information System. The diagnosis time, infection route, and clinical characteristics of the cases were obtained from the case investigation reports. Descriptive epidemiological methods were used to analyze the temporal, spatial, demographic distributions, and clinical characteristics of human brucellosis. Brucella species were identified using agglutination tests with bacterial suspension and A/M antigen-positive serum. ResultsA total of 2 193 cases of human brucellosis were confirmed and clinically diagnosed in Tangshan City from 2016 to 2023, with the peak incidence occured from March to August, and which exhibited distinct geographic distribution patterns. The highest incidence rate was found in people aged 60‒<70 years. The occupation of cases were primarily farmers. The incidence rate in males (528/100 000) was higher than that in females (184/100 000). All cases had confirmed exposure to infected animals or contaminated animal products. ConclusionThe epidemic of human brucellosis in Tangshan exhibited an overall steady downward trend from 2016 to 2023, except for a slight increase in 2016 and 2021, with the incidence rate controlled at 289/100 000‒335/100 000. The prevention and control situation of human brucellosis still remains severe, with the highest incidence rate in the eastern region of Tangshan, which are characterized by the breeding, slaughtering, and processing of cattle and sheep. Therefore, it it is necessary to enhance the prevention and control of human brucellosis among the personnel engaged in these industries in the eastern areas.

BACKGROUND: Postoperative pulmonary complications (PPCs) are major adverse events in neurosurgical patients. This study aimed to develop and validate machine learning models predicting PPCs after neurosurgery. METHODS: PPCs were defined according to the European Perioperative Clinical Outcome standards as occurring within 7 postoperative days. Data of cases meeting inclusion/exclusion criteria were extracted from the anesthesia information management system to create three datasets: The development (data of Huashan Hospital, Fudan University from 2018 to 2020), temporal validation (data of Huashan Hospital, Fudan University in 2021) and external validation (data of other three hospitals in 2023) datasets. Machine learning models of six algorithms were trained using either 35 retrievable and plausible features or the 11 features selected by Lasso regression. Temporal validation was conducted for all models and the 11-feature models were also externally validated. Independent risk factors were identified and feature importance in top models was analyzed. RESULTS: PPCs occurred in 712 of 7533 (9.5%), 258 of 2824 (9.1%), and 207 of 2300 (9.0%) patients in the development, temporal validation and external validation datasets, respectively. During cross-validation training, all models except Bayes demonstrated good discrimination with an area under the receiver operating characteristic curve (AUC) of 0.840. In temporal validation of full-feature models, deep neural network (DNN) performed the best with an AUC of 0.835 (95% confidence interval [CI]: 0.805-0.858) and a Brier score of 0.069, followed by Logistic regression (LR), random forest and XGBoost. The 11-feature models performed comparable to full-feature models with very close but statistically significantly lower AUCs, with the top models of DNN and LR in temporal and external validations. An 11-feature nomogram was drawn based on the LR algorithm and it outperformed the minimally modified Assess respiratory RIsk in Surgical patients in CATalonia (ARISCAT) and Laparoscopic Surgery Video Educational Guidelines (LAS VEGAS) scores with a higher AUC (LR: 0.824, ARISCAT: 0.672, LAS: 0.663). Independent risk factors based on multivariate LR mostly overlapped with Lasso-selected features, but lacked consistency with the important features using the Shapley additive explanation (SHAP) method of the LR model. CONCLUSIONS: The developed models, especially the DNN model and the nomogram, had good discrimination and calibration, and could be used for predicting PPCs in neurosurgical patients. The establishment of machine learning models and the ascertainment of risk factors might assist clinical decision support for improving surgical outcomes. TRIAL REGISTRATION ChiCTR 2100047474; https://www.chictr.org.cn/showproj.html?proj=128279 .
Adult ; Aged ; Female ; Humans ; Male ; Middle Aged ; Algorithms ; Lung Diseases/etiology* ; Machine Learning ; Neurosurgical Procedures/adverse effects* ; Postoperative Complications/diagnosis* ; Risk Factors ; ROC Curve