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 paper comprehensively discusses on the potential neurobiological mechanisms of acupuncture in the treatment of tobacco dependence， focusing on three important aspects， including acupuncture's regulation of tobacco dependence behavior， effects of acupuncture on withdrawal syndrome， and the role of acupuncture in preventing relapse. It is found that acupuncture can inhibit drug-seeking behavior by regulating the reward pathway and related neurons， such as dopamine， thus modulating tobacco dependence behavior. It also alleviates withdrawal symptoms by improving the oral environment of smokers and reducing negative emotions after quitting. Furthermore， acupuncture can prevent relapse by decreasing brain network activity related to smoking cravings and improving cognitive brain functions like addiction memory. Currently， research on the specific neurobiological mechanism of acupuncture in treating tobacco dependence and the involved neural circuits is limited. Future research directions are proposed， including the evaluation of clinical effects， exploration of specific therapeutic mechanisms， investigation of brain pathology， and strengthening the exploration of brain functions. Additionally， combining modern technologies to clarify the neural circuits involved in acupuncture intervention will provide a basis for acupuncture treatment of tobacco addiction.

Alzheimer’s disease (AD) is a prevalent neurodegenerative condition characterized by progressive cognitive decline and memory loss. As the incidence of AD continues to rise annually, researchers have shown keen interest in the active components found in natural plants and their neuroprotective effects against AD. Quercetin, a flavonol widely present in fruits and vegetables, has multiple biological effects including anticancer, anti-inflammatory, and antioxidant. Oxidative stress plays a central role in the pathogenesis of AD, and the antioxidant properties of quercetin are essential for its neuroprotective function. Quercetin can modulate multiple signaling pathways related to AD, such as Nrf2-ARE, JNK, p38 MAPK, PON2, PI3K/Akt, and PKC, all of which are closely related to oxidative stress. Furthermore, quercetin is capable of inhibiting the aggregation of β‑amyloid protein (Aβ) and the phosphorylation of tau protein, as well as the activity of β‑secretase 1 and acetylcholinesterase, thus slowing down the progression of the disease.The review also provides insights into the pharmacokinetic properties of quercetin, including its absorption, metabolism, and excretion, as well as its bioavailability challenges and clinical applications. To improve the bioavailability and enhance the targeting of quercetin, the potential of quercetin nanomedicine delivery systems in the treatment of AD is also discussed. In summary, the multifaceted mechanisms of quercetin against AD provide a new perspective for drug development. However, translating these findings into clinical practice requires overcoming current limitations and ongoing research. In this way, its therapeutic potential in the treatment of AD can be fully utilized.

Objective To investigate serum β2-MG, sCHE, and PSGL-1 expression in patients with esophageal cancer and their relationship to lung infection after mediastinoscopy. Methods A total of 118 patients with esophageal cancer were selected and divided into infected and uninfected groups according to whether they developed lung infection after surgery. An automatic microbiological identification system was used to detect the pathogenic bacteria of lung infection. ELISA was used to detect the levels of β2-MG, sCHE, and PSGL-1. Multivariate logistic regression was used to analyze the influencing factors of postoperative lung infection in patients with esophageal cancer. ROC curves were plotted to analyze the assessment value of serum β2-MG, sCHE, and PSGL-1 on postoperative lung infection. Results Fifty-two strains of bacteria were isolated from the sputum of 38 patients with postoperative lung infections, and these included 35 (67.31%) Gram-negative, 14 (26.92%) Gram-positive, and 3 (5.77%) fungal strains. The difference in long-term smoking history between the infected and uninfected groups was statistically significant (P<0.05). Serum β2-MG and PSGL-1 levels were significantly higher and sCHE levels were significantly lower in the infected group than in the uninfected group (P<0.05). Serum β2-MG and PSGL-1 levels were sequentially higher (P<0.05) and sCHE levels were sequentially lower (P<0.05) in the mild, moderate, and severe lung infection groups. Long-term smoking history, β2-MG, and PSGL-1 were risk factors affecting postoperative lung infection in patients with esophageal cancer (P<0.05), and sCHE was a protective factor (P<0.05). The AUCs of serum β2-MG, sCHE, and PSGL-1 for assessing postoperative lung infections were 0.807, 0.845, and 0.800, respectively, and the AUC of the three combined factors for assessing postoperative lung infections was 0.954, which was superior to that assessed individually (Z_{combination vs. β2-MG}=2.576, Z_{combination vs. sCHE}=2.623, Z_{combination vs. PSGL-1}=2.574, all P<0.05). Conclusion The serum levels of β2-MG and PSGL-1 increase and the sCHE level decreases in patients with esophageal cancer and postoperative pulmonary infection, which are also related with lung infection. Combined testing can improve the evaluation value of postoperative pulmonary infection in patients.

ObjectiveStudies have shown that nuciferine has anti-cerebral ischemia effect， but the specific mechanism of action has not been elaborated. Based on the transcriptome results， the pharmacological mechanism of nuciferine against cerebral ischemia was analyzed from multiple dimensions including tissue， cell， pathological process， biological process and signaling pathway. MethodsThirty SD rats were randomly divided into the sham group， model group and nuciferine group（40 mg·kg^-1） according to weight. Except for the sham group， the model of middle cerebral artery occlusion（MCAO） was established by thread embolization method after 30 min of administration in the other two groups. Twenty-four hours after surgery， transcriptome sequencing was used to detect the gene expression profiles in the cortex penumbra of rat cerebral tissue， and gene ontology（GO） and kyoto encyclopedia of genes and genomes（KEGG） pathway enrichment analysis were performed for differentially expressed genes. The mechanismof nuciferine against cerebral ischemia was analyzed from 5 dimensions of tissue， cell， pathological process， biological process and signaling pathway by the transcriptome-based multi-scale network pharmacology platform（TMNP）. ResultsTranscriptome sequencing and gene quantitative analysis showed that 667 genes were significantly reversed by nuciferine. Further enrichment analysis of KEGG and GO suggested that the pathways of nuciferine involved regulating stress response， ion transport， cell proliferation and differentiation， and synaptic function. TMNP research found that at the tissue level， nuciferine could significantly improve the cerebral tissue injury caused by ischemia. At the cellular and pathological levels， nuciferine could play an anti-cerebral ischemia role by improving the state of various nerve cells， mobilizing immune cells， regulating inflammation. And at the level of biological processes and signaling pathways， nuciferine mainly acted on the processes such as vascular remodeling， inflammation-related signaling pathways， and synaptic signaling. ConclusionCombined with the results of transcriptome sequencing， gene quantitative analysis and TMNP， the mechanism of nuciferine against cerebral ischemia may be related to processes such as intervening in stress response and inflammation， affecting vascular remodeling and regulating synaptic function. These results can provide a basis and reference for further study of the pharmacological mechanism of nuciferine against cerebral ischemia.

Epilepsy is a chronic neurological disease caused by abnormal synchronous discharge of the brain, which is characterized by recurrent and transient neurological abnormalities, mainly manifested as loss of consciousness and limb convulsions, and can occur in people of all ages. At present, anti-epileptic drugs (AEDs) are still the main means of treatment, but their efficacy is limited by the problem of drug resistance, and long-term use can cause serious side effects, such as cognitive dysfunction and vital organ damage. Although surgical resection of epileptic lesions has achieved certain results in some patients, the high cost and potential risk of neurological damage limit its scope of application. Therefore, the development of safe, accurate and personalized non-invasive treatment strategies has become one of the key directions of epilepsy research. In recent years, photobiomodulation (PBM) has gained significant attention as a promising non-invasive therapeutic approach. PBM uses light of specific wavelengths to penetrate tissues and interact with photosensitive molecules within cells, thereby modulating cellular metabolic processes. Research has shown that PBM can enhance mitochondrial function, promote ATP production, improve meningeal lymphatic drainage, reduce neuroinflammation, and stimulate the growth of neurons and synapses. These biological effects suggest that PBM not only holds the potential to reduce the frequency of seizures but also to improve the metabolic state and network function of neurons, providing a novel therapeutic avenue for epilepsy treatment. Compared to traditional treatment methods, PBM is non-invasive and avoids the risks associated with surgical interventions. Its low risk of significant side effects makes it particularly suitable for patients with drug-resistant epilepsy, offering new therapeutic options for those who have not responded to conventional treatments. Furthermore, PBM’s multi-target mechanism enables it to address a variety of complex etiologies of epilepsy, demonstrating its potential in precision medicine. In contrast to therapies targeting a single pathological mechanism, PBM’s multifaceted approach makes it highly adaptable to different types of epilepsy, positioning it as a promising supplementary or alternative treatment. Although animal studies and preliminary clinical trials have shown positive outcomes with PBM, its clinical application remains in the exploratory phase. Future research should aim to elucidate the precise mechanisms of PBM, optimize light parameters, such as wavelength, dose, and frequency, and investigate potential synergistic effects with other therapeutic modalities. These efforts will be crucial for enhancing the therapeutic efficacy of PBM and ensuring its safety and consistency in clinical settings. This review summarizes the types of epilepsy, diagnostic biomarkers, the advantages of PBM, and its mechanisms and potential applications in epilepsy treatment. The unique value of PBM lies not only in its multi-target therapeutic effects but also in its adaptability to the diverse etiologies of epilepsy. The combination of PBM with traditional treatments, such as pharmacotherapy and neuroregulatory techniques, holds promise for developing a more comprehensive and multidimensional treatment strategy, ultimately alleviating the treatment burden on patients. PBM has also shown beneficial effects on neural network plasticity in various neurodegenerative diseases. The dynamic remodeling of neural networks plays a critical role in the pathogenesis and treatment of epilepsy, and PBM’s multi-target mechanism may promote brain function recovery by facilitating neural network remodeling. In this context, optimizing optical parameters remains a key area of research. By adjusting parameters such as wavelength, dose, and frequency, researchers aim to further enhance the therapeutic effects of PBM while maintaining its safety and stability. Looking forward, interdisciplinary collaboration, particularly in the fields of neuroscience, optical engineering, and clinical medicine, will drive the development of PBM technology and facilitate its transition from laboratory research to clinical application. With the advancement of portable devices, PBM is expected to provide safer and more effective treatments for epilepsy patients and make a significant contribution to personalized medicine, positioning it as a critical component of precision therapeutic strategies.

ObjectiveThis study leverages structural data from antigen-antibody complexes of the influenza A virus neuraminidase (NA) protein to investigate the spatial recognition relationship between the antigenic epitopes and antibody paratopes. MethodsStructural data on NA protein antigen-antibody complexes were comprehensively collected from the SAbDab database, and processed to obtain the amino acid sequences and spatial distribution information on antigenic epitopes and corresponding antibody paratopes. Statistical analysis was conducted on the antibody sequences, frequency of use of genes, amino acid preferences, and the lengths of complementarity determining regions (CDR). Epitope hotspots for antibody binding were analyzed, and the spatial structural similarity of antibody paratopes was calculated and subjected to clustering, which allowed for a comprehensively exploration of the spatial recognition relationship between antigenic epitopes and antibodies. The specificity of antibodies targeting different antigenic epitope clusters was further validated through bio-layer interferometry (BLI) experiments. ResultsThe collected data revealed that the antigen-antibody complex structure data of influenza A virus NA protein in SAbDab database were mainly from H3N2, H7N9 and H1N1 subtypes. The hotspot regions of antigen epitopes were primarily located around the catalytic active site. The antibodies used for structural analysis were primarily derived from human and murine sources. Among murine antibodies, the most frequently used V-J gene combination was IGHV1-12*01/IGHJ2*01, while for human antibodies, the most common combination was IGHV1-69*01/IGHJ6*01. There were significant differences in the lengths and usage preferences of heavy chain CDR amino acids between antibodies that bind within the catalytic active site and those that bind to regions outside the catalytic active site. The results revealed that structurally similar antibodies could recognize the same epitopes, indicating a specific spatial recognition between antibody and antigen epitopes. Structural overlap in the binding regions was observed for antibodies with similar paratope structures, and the competitive binding of these antibodies to the epitope was confirmed through BLI experiments. ConclusionThe antigen epitopes of NA protein mainly ditributed around the catalytic active site and its surrounding loops. Spatial complementarity and electrostatic interactions play crucial roles in the recognition and binding of antibodies to antigenic epitopes in the catalytic region. There existed a spatial recognition relationship between antigens and antibodies that was independent of the uniqueness of antibody sequences, which means that antibodies with different sequences could potentially form similar local spatial structures and recognize the same epitopes.

[摘 要] 目的：探讨同源框蛋白C4（HOXC4）在胃癌组织和细胞中的表达及其对胃癌细胞增殖、迁移与侵袭的作用及其机制。方法：收集2020年5月至2021年4月期间在南阳市第一人民医院肿瘤科手术切除的16例进展期胃癌患者的癌及癌旁组织标本，以及人胃正常上皮细胞GES-1和胃癌细胞AGS、SGC-790和MGC-803，采用WB法检测胃癌组织和细胞中HOXC4的表达。通过RNA干扰技术对SGC-790及AGS细胞中HOXC4进行敲低或过表达，实验分为sh-HOXC4#1组、sh-HOXC4#2组、sh-Con组、sh-HOXC4 + pc-integrin β1组、pc-HOXC4组、pc-Con组、pc-HOXC4 + pc-integrin β1组。利用EdU、CCK-8、Transwell实验分别检测敲低或过表达HOXC4对各组细胞活力、增殖、侵袭、迁移和integrin β1表达的影响。用敲低HOXC4的胃癌AGS细胞构建荷瘤小鼠模型，观察敲低HOXC4对移植瘤体积及组织中Ki67和integrin β1蛋白表达的影响。结果：胃癌组织和细胞中HOXC4的表达均显著上调（均P < 0.01）。与sh-Con组相比，sh-HOXC4#1组和sh-HOXC4#2组SGC-790及AGS细胞中HOXC4、integrin β1蛋白表达水平，以及细胞的活力、增殖、迁移及侵袭能力均显著降低（均P < 0.01）。与sh-HOXC4组相比，sh-HOXC4 + pc-integrin β1组细胞活力、增殖、迁移及侵袭能力均显著增加（均P < 0.01）；与pc-Con组相比，pc-HOXC4组细胞活力、侵袭及迁移能力均显著增加（均P < 0.01）；与pc-HOXC4组相比，pc-HOXC4 + pc-integrin β1组细胞活力、迁移及侵袭能力均显著降低（均P < 0.01）。与sh-Con组相比，sh-HOXC4#1组和sh-HOXC4#2组小鼠移植瘤生长缓慢、体积变小，组织中Ki67和integrin β1表达均显著降低（均P < 0.01）。结论：HOXC4在胃癌组织与细胞中表达上调，其通过激活integrin β1信号促进胃癌细胞的增殖、迁移与侵袭。

Objective To predict the radiation impact of discharging wastewater containing uranium within the specified limit generated during the normal operation of a new production line at a nuclear fuel plant on the receiving water body and its downstream, and to provide a reference for the management of radioactive liquid effluent discharge from nuclear facilities. Methods Based on the technical guidelines for environmental impact assessment, literature on radiation environmental impact assessment, and data collected from on-site investigations, appropriate hydrological parameters and prediction models were selected to analyze and predict the variation pattern of radioactive nuclide uranium along the receiving water body and the radiation exposure of nearby residents. Results The maximum increase in uranium concentration in the receiving water body and its downstream caused by the discharge of uranium-containing wastewater was 1.14 μg/L. The maximum predicted concentration was 2.75 μg/L after adding the background data of the water body. The resulting maximum individual annual effective dose for the public was 1.49 × 10⁻⁴ mSv/a. Conclusion The maximum predicted uranium concentration in the receiving water body and its downstream is lower than the uranium concentration limit of 30 μg/L specified in the Standards for Drinking Water Quality (GB 5749-2022). The maximum individual annual effective dose for the public is much lower than the control value of 0.2 mSv/a specified in the Radiation Protection Regulations for Uranium Processing and Fuel and Fuel Manufacturing Facilities (EJ 1056-2018). The radiation impact is acceptable.

Objective: To explore the feasibility of synthetic magnetic resonance imaging (syMRI) combined with clinicopathological characteristics for the pre-treatment prediction of chemoradiotherapy (CRT) response in advanced nasopharyngeal carcinoma (ANPC). Materials and Methods: Patients with ANPC treated with CRT between September 2020 and June 2022 were retrospectively enrolled and categorized into response group (RG, n = 95) and non RGs (NRG, n = 32) based on the Response Evaluation Criteria in Solid Tumors (RECIST) 1.1. The quantitative parameters from pre-treatment syMRI (longitudinal [T1] and transverse [T2] relaxation times and proton density [PD]), diffusion-weighted imaging (apparent diffusion coefficient [ADC]), and clinicopathological characteristics were compared between RG and NRG. Logistic regression analysis was applied to identify parameters independently associated with CRT response and to construct a multivariable model. The areas under the receiveroperating characteristic curve (AUC) for various diagnostic approaches were compared using the DeLong test. Results: The T1, T2, and PD values in the NRG were significantly lower than those in the RG (all P < 0.05), whereas no significant difference was observed in the ADC values between these two groups. Clinicopathological characteristics (Epstein–Barr virus [EBV]-DNA level, lymph node extranodal extension, clinical stage, and Ki-67 expression) exhibited significant differences between the two groups. Logistic regression analysis showed that T1, PD, EBV-DNA level, clinical stage, and Ki-67 expression had significant independent relationships with CRT response (all P < 0.05). The multivariable model incorporating these five variables yielded AUC, sensitivity, and specificity values of 0.974, 93.8% (30/32), and 91.6% (87/95), respectively. Conclusion SyMRI may be used for the pretreatment prediction of CRT response in ANPC. The multivariable model incorporating syMRI quantitative parameters and clinicopathological characteristics, which were independently associated with CRT response, may be a new tool for the pretreatment prediction of CRT response.