ObjectiveTo evaluate the antitumor activity of Periplaneta americana extract（PAE） against human-derived lung adenocarcinoma organoids（LUAD-PDOs） and to elucidate its potential mechanism based on transcriptomics. MethodsFresh tumor and adjacent normal tissues from patients with LUAD were collected to construct LUAD-PDOs and normal lung organoid（Nor-PDOs） models using 3D organoid culture technology. The effective intervention concentration of PAE was determined using the cell counting kit-8（CCK-8） assay. Experimental groups included the model group（LUAD-PDOs）， normal group， model administration group（LUAD-PDOs+PAE）， and normal administration group（Nor-PDOs+PAE）. Hematoxylin-eosin（HE） staining was used to observe the pathological structures of PDOs， immunohistochemistry（IHC） was performed to detect the expressions of the proliferation marker Ki-67 and lung adenocarcinoma differentiation markers cytokeratin-7（CK-7） and Napsin A， TUNEL staining was applied to detect cell apoptosis. RNA sequencing（RNA-Seq） was conducted to identify differentially expressed genes（DEGs）， followed by Gene Ontology（GO）， Kyoto Encyclopedia of Genes and Genomes（KEGG）， and Gene Set Enrichment Analysis（GSEA）， alongside protein-protein interaction（PPI） network analysis to screen core mechanisms. Finally， key targets were validated by integrating external database analysis with immunofluorescence（IF）. ResultsNor-PDOs and LUAD-PDOs that highly recapitulated the pathological characteristics of the primary tissues were successfully established. The CCK-8 assay determined that the effective intervention concentration of PAE was 16 g·L^-1. Morphological observation showed that Nor-PDOs exhibited lumen-forming structures， whereas LUAD-PDOs displayed dense， solid structures. CCK-8 and TUNEL assays revealed that， compared with the model group， PAE intervention inhibited the proliferation of LUAD-PDOs and promoted apoptosis in LUAD cells， while showing no significant effect on the viability of Nor-PDOs. Transcriptomic analysis identified 719 DEGs that were significantly reversed after PAE intervention（347 up-regulated and 372 down-regulated）（P<0.05）. GO enrichment analysis indicated that DEGs in the model administration group were significantly enriched in biological processes related to cell cycle regulation compared to the model group. KEGG pathway analysis revealed that PAE affected pathways related to proliferation and metabolism， including pathways in cancer and the p53 signaling pathway. GSEA further confirmed that PAE significantly enhanced the activity of the p53 signaling pathway（P<0.05）. PPI network analysis indicated that breast cancer type 1 susceptibility protein（BRCA1） and checkpoint kinase 1（CHEK1） were the core down-regulated targets in the p53 pathway. IF verified the high expression of BRCA1 and CHEK1 in LUAD-PDOs and their significant downregulation after PAE intervention（P<0.05）. Furthermore， survival analysis based on The Cancer Genome Atlas（TCGA） database indicated that low expression of BRCA1 and CHEK1 was significantly associated with prolonged overall survival in patients with LUAD（P<0.05）. ConclusionPAE effectively inhibits proliferation of LUAD-PDOs and promotes their apoptosis， its anti-tumor mechanism is potentially associated with the activation of the p53 signaling pathway， with BRCA1 and CHEK1 genes likely serving as key downstream targets for the effects of PAE.

The research and development of innovative drug have progressed remarkably, but the long development circle and high failure rate have become the bottleneck. Drug repurposing, discovering new indications of approved drugs, is a strategy to overcome these obstacles. By exploring new indications for approved drugs, rapid progress has been made in basic research and clinical translation in recent years. Rich resources of drugs, proven security, efficient development workflow and reduced cost are core advantages of this strategy, making the strategy a crucial direction of optimizing the pipeline of drug research and development. This review systematically summarizes drug repurposing cases that have received clinical approval over the past five years, and proposes core strategies for drug repurposing, including approaches based on targets, pathways, drug similarity, post-treatment phenotypes, and clinical side effects, aiming to provide some strategic guidance for drug repurposing efforts.

Objective To explore the impact of wearable devices in assisting disease monitoring on heart-focused anxiety in patients with tachyarrhythmias. Methods A cross-sectional study design was conducted. 305 patients with tachyarrhythmias who attended the department of cardiology of Zhongshan Hospital, Fudan University in Shanghai from July 2025 to December 2025 were enrolled as the research subjects, and clinical data of patients were collected. Univariate analysis and multiple stepwise regression analysis were used to analyze the impact of wearable devices in assisting disease monitoring on patients’ heart-focused anxiety. Results The mean score of heart-focused anxiety in the 305 patients with tachyarrhythmias was 33.16±9.70. Among them, 104(34.10%) patients used wearable devices in assisting disease monitoring. The results of univariate analysis and multiple stepwise regression showed that the use of wearable devices in assisting disease monitoring was an influencing factor for heart-focused anxiety (P＜0.05), and the patients who used wearable devices in assisting disease monitoring had a significantly lower level of heart-focused anxiety (P＜0.05). Conclusions The use of wearable devices in assisting disease monitoring is associated with a lower level of heart-focused anxiety in patients with tachyarrhythmias. Medical staff can guide patients to rationally use wearable devices in assisting disease monitoring on the basis of evaluating their needs and device operation capabilities.

Objective:To estimate the radiation dose to caregivers and the public from 177Lu- peptide receptor radionuclide therapy (PRRT) for pediatric neuroblastoma patients and determine the duration of contact restrictions, in order to provide a reference for relevant radiation protection measures. Methods:A retrospective study was conducted by collecting data from 18 pediatric neuroblastoma patients, aged between 3 and 13 (6.72±2.72), who received 177Lu-1, 4, 7, 10-tetraazacyclododecane-1, 4, 7, 10-tetraacetic acid-D-Phe1-Tyr3-Thr8-octreotide (DOTATATE) treatment at the Nuclear Medicine Department of Shandong Cancer Hospital from June 2023 to July 2023. Absorbed dose rate in air at 0, 0.1, 0.5, 1 and 2 m from the patients was measured using a radiation-survey at 1, 4, 24, 48 and 96 h after administration. The whole-body region of interest was delined using HERMES software. Subsequently, curve regression fitting was performed using a biexponential function model. By incorporating hypothesized social contact durations, the effective doses received by family members and the public in contact with patients were estimated. Additionally, MIM software was used to outline the whole-body VOI to obtain the total volume of lesions, and the Pearson or Spearman correlation coefficient was employed to analyze the relationship between the absorbed dose rate in air and clinical indicators as well as the total volume of lesions. Results:The 177Lu-DOTATATE administration dose was (4 353.42±1 451.51) MBq. All patients were discharged from hospital 24 h after 177Lu-DOTATATE administration. At the time of discharge, patients had excreted (76.70±3.99)% of the administered activity, and the absorbed dose rate in air at 0.1, 1 and 2 m from the patients were (32.74±6.98), 3.68(3.01, 4.70) and (1.22±0.51) μSv/h, respectively. After being discharged, the radiation doses to caregivers from children aged 2-5 years and 5-13 years were (2.47±1.80) mSv and (0.88±0.47) mSv, respectively. The contact restriction duration was 2 d for nighttime sleeping with family members and 1 d for contact with other children. On the day of discharge, patients should limit their time on public transportation within 4 h and do not need to restrict private transportation. Conclusions:To ensure the effective dose kept within the safety limits stipulated by current regulations, it is necessary to implement contact restrictions for patients’ family members and the public. After implementing preventive measures, 177Lu-DOTATATE treatment is a safe radionuclide therapeutic option.

Objective:To compare the consistency of microarray chemiluminescent protein chip and immunoblotting in the autoantibody spectrum of patients and the diagnostic efficacy of systemic lupus erythematosus(SLE), and to explore the correlation between the detection results of protein microarray and clinical indicators and lymphocyte subsets.Methods:Serum autoantibodies in 649 samples collected between December 2023 and December 2024 in Nanjing Drum Tower Hospital were analyzed using the microarray chemiluminescent protein chip method, with 401 samples simultaneously tested by immunoblotting. Kappa coefficient assessed inter-method consistency. Diagnostic performance was compared via ROC curves. Spearman correlation analysis evaluated relationships between autoantibody levels and SLEDAI-2000 scores, clinical parameters, and lymphocyte subsets.Results:The two methods demonstrated good consistency across 14 antinuclear antibodies, with optimal agreement for anti-SSA/Ro ( Kappa=0.845, P<0.001), anti-SSB ( Kappa=0.825, P<0.001), and anti-CENP B ( Kappa=0.851, P<0.001). The protein chip method significantly improved SLE diagnostic efficacy, particularly for anti-dsDNA (AUC difference=0.291, P<0.001) and anti-Sm antibodies (AUC difference=0.295, P<0.001). Combined detection of anti-SSA/Ro and anti-nRNP/Sm antibodies achieved superior diagnostic performance (AUC=0.927). Anti-dsDNA, anti-histone, and anti-nucleosome antibodies positively correlated with SLEDAI-2000 ( r=0.408, 0410, 0.384, all P<0.001), complement ( P<0.001), and 24-hour urinary protein ( r=0.374, 0.387, 0.301, all P<0.001). Immunological analysis showed that the proportion of NK cells was generally negatively correlated with antinuclear antibodies such as anti-dsDNA ( r=-0.352, P<0.001) and anti-Sm ( r=-0.328, P<0.001) antibodies. Meanwhile, the proportion of CD8 + T cells was positively correlated with anti-nRNP/Sm ( r=0.229, P=0.002) and anti-Sm antibodies ( r=0.211, P=0.005). The proportion of CD4 + T cells was negatively correlated with anti-SSA/Ro ( r=-0.239, P<0.001), while the proportion of B cells was positively correlated with anti-dSDNA antibody ( r=0.300, P<0.001). Conclusion:The protein chip method showed strong consistency with immunoblotting for detecting 14 autoantibodies but demonstrated superior SLE diagnostic efficacy. The combined use of multiple detection methods can enhance the reliability of clinical diagnosis.

Pain assessment in children is vital in clinical practice. Accurate evaluation of pain intensity in children is the prerequisite for implementing effective analgesic interventions, it is necessary to chose age-specific assessment tools tailored to developmental stages of children. The degrees of patin reported by children themselves are the gold standard for evaluation, and self-assessment should be prioritized when feasible. In addition, behavioral and physiological assessments also show good reliability and validity. This review summarizes current domestic and international researches on pediatric pain assessment tools and their clinical applications, aiming to provide reference for optimizing pain evaluation in pediatric practice.

Objective:To explore the application effects of a method combining progressive case study and fishbone diagram in clinical teaching of interns in general surgery, and evaluate its impact on medical students' theoretical knowledge mastery, clinical practice ability development, and systematic thinking cultivation.Methods:Sixty undergraduate clinical medicine students who interned in the Department of General Surgery from July 2022 to December 2023 were selected as the research subjects and randomly divided into a control group ( n=30) and an observation group ( n=30). The control group received traditional case-based teaching through centralized lectures, group discussions, and review/Q&A sessions. The observation group received an integrated teaching approach combining progressive case study and fishbone diagram through the design of progressive cases and fishbone diagrams. Teaching effectiveness was evaluated through theoretical assessment, practical assessment, and teaching satisfaction survey. SPSS 22.0 was used for t-test and χ2 test. Results:The total score of theoretical assessments for the observation group interns was higher than that of the control group [(86.97±4.60) vs. (66.06±5.96), t=-17.79, P<0.001]. The differences in scores of diagnosis and treatment standards [(17.03±1.82) vs. (14.07±2.35)] and differential diagnosis [(12.85±1.42) vs. (8.92±2.37)] were particularly significant. In the practical assessments, the total score of the observation group interns [(90.19±5.04) vs. (68.63±4.30), t=-17.82, P<0.001] and their scores in individual assessments were higher than those of the control group, especially in acute abdomen evaluation [(18.23±1.72) vs. (14.37±2.05)], laparoscopic spatial positioning [(8.83±0.95) vs. (5.92±1.38)], and intraoperative emergency management [(8.95±0.97) vs. (6.05±1.23)]. The satisfaction scores of the observation group interns were higher than those of the control group ( P<0.001), with the greatest improvement in clinical thinking [(4.65±0.61) vs. (3.10±0.71)] and teacher-student interaction quality [(4.72±0.53) vs. (3.11±0.63)]. Conclusions:The teaching method combining progressive case study and fishbone diagram significantly improved interns' theoretical assessment scores, practical operation ability, and clinical decision-making level through the dynamic presentation of case evolution processes and the application of structured analysis tools, and also enhanced the teaching satisfaction.

Mutations in isocitrate dehydrogenase 1(IDH1)can abnormally produce the oncometabolite D-2-hydroxyglutarate(D2HG),which in turn remodels the tumor immune microenvironment.In recent years,it has become a key target in the research on the interaction between tumor metabolism and immunity.D2HG competitively inhibits endogenous α-ketoglutarate-dependent dioxygenases,leading to DNA histone hypermethylation and cell differentiation arrest,thus promoting tumorigenesis,development,metastasis,and drug resistance.Meanwhile,D2HG suppresses T-cell function,promotes myeloid cell expansion and macrophage polarization,weakens immune surveillance,and creates an immunosuppressive state that affects the response to immunotherapy.In various tumors,such as glioma,acute myeloid leukemia,and cholangiocarcinoma,IDH1 mutations exhibit heterogeneity and different prognostic characteristics.Currently,small-molecule inhibitors targeting IDH1 mutations,such as ivosidenib and vorasidenib,can partially reverse immunosuppression by reducing D2HG levels and have shown certain efficacy in clinical trials.However,these inhibitors face challenges including efficacy differences,drug resistance,and safety concerns.Combination therapies with IDH1 inhibitors aim to synergistically reverse the metabolic-epigenetic-immune triple-suppression network and enhance the anti-tumor effects,attracting extensive attention.This article reviews the tumor immune regulatory network mediated by IDH1-mutation-induced D2HG metabolism and comprehensively summarizes progress in related drug development,providing new references and ideas for tumor prevention and treatment.

In the context of the rapid development of 5G technology， the development of artificial intelligence （AI） in traditional Chinese medicine （TCM） faces new opportunities and challenges. Focusing on how to uphold tradition while innovating in the development of AI in TCM， starting from the current development status of AI in Chinese medicine， including the integration of four diagnostic methods， syndrome differentiation and treatment， auxiliary diagnosis and treatment， research and development of Chinese herbal medicine， prevention and treatment of diseases， knowledge inheritance， and other aspects， this paper discussed the support of policies and technical advancements， as well as development opportunities such as increased demand for health. Regarding machine ethics， data ethics， regulatory review， and other aspects， it also proposed some suggestions that the training algorithm should be improved to assist medical work； data ownership should be clarified to ensure data security； and an AI ethics committee should be set up to improve the review system， aiming to maximize the advantages of smart healthcare and accelerate the modernization of TCM for the benefit of patients and the service of human health.

BACKGROUND:In recent years,deep learning technologies have been increasingly applied in the field of oral medicine,enhancing the efficiency and accuracy of oral imaging analysis and promoting the rapid development of intelligent oral medicine. OBJECTIVE:To elaborate the current research status,advantages,and limitations of deep learning based on oral imaging in the diagnosis and treatment decision-making of oral diseases,as well as future prospects,exploring new directions for the transformation of oral medicine under the backdrop of deep learning technology. METHODS:PubMed was searched for literature related to deep learning in oral medical imaging published from January 2017 to January 2024 with the search terms"deep learning,artificial intelligence,stomatology,oral medical imaging."According to the inclusion criteria,80 papers were finally included for review. RESULTS AND CONCLUSION:(1)Classic deep learning models include artificial neural networks,convolutional neural networks,recurrent neural networks,and generative adversarial networks.Scholars have used these models in competitive or cooperative forms to achieve more efficient interpretation of oral medical images.(2)In the field of oral medicine,the diagnosis of diseases and the formulation of treatment plans largely depend on the interpretation of medical imaging data.Deep learning technology,with its strong image processing capabilities,aids in the diagnosis of diseases such as dental caries,periapical periodontitis,vertical root fractures,periodontal disease,and jaw cysts,as well as preoperative assessments for procedures such as third molar extraction and cervical lymph node dissection,helping clinicians improve the accuracy and efficiency of decision-making.(3)Although deep learning is promising as an important auxiliary tool for the diagnosis and treatment of oral diseases,it still has certain limitations in model technology,safety ethics,and legal regulation.Future research should focus on demonstrating the scalability,robustness,and clinical practicality of deep learning,and finding the best way to integrate automated deep learning decision support systems into routine clinical workflows.