ObjectiveRetinal vein occlusion （RVO） is the second most common vascular disease leading to vision loss. Since its pathogenesis remains unclear， current Western medical treatments primarily target complications such as macular edema and neovascularization. The main therapeutic approaches include intravitreal injections of anti-vascular endothelial growth factor （VEGF） agents or corticosteroids， laser photocoagulation， and pars plana vitrectomy. However， these treatments cannot fully reverse disease progression or structural damage. Traditional Chinese medicine （TCM） has unique advantages in the clinical diagnosis and treatment of RVO， and integrated Chinese and Western medicine approaches may offer better clinical outcomes. This study， based on the clinical manifestations of RVO， systematically reviews the existing literature and evaluates the alignment of current RVO animal models with clinical manifestations. The aim is to identify the characteristics and limitations of existing models and provide recommendations and prospects for developing RVO animal models featuring the combination of disease and syndrome. MethodsDatabases including CNKI， Wanfang Data， PubMed， and Web of Science were searched with the keywords of "retinal vein occlusion" and "animal model". Model characteristics were assessed based on the diagnostic criteria for diseases and syndromes in both TCM and Western medicine. The alignment of each model with clinical manifestations was analyzed and evaluated. ResultsThe available RVO models were primarily established via methods such as laser photocoagulation， photodynamic therapy， diathermy， intravitreal drug injection， and mechanical modeling. These models demonstrated moderate overall alignment with clinical manifestations， mainly reflecting disease characteristics. However， they generally lack representation of TCM syndrome features. ConclusionExisting RVO models are predominantly based on Western medicine and lack TCM syndrome features. Western medical treatments for RVO have certain limitations， while syndrome differentiation and treatment in TCM offer potential advantages. Future research should focus on developing disease-syndrome integrated animal models that incorporate both pathological features and TCM syndrome characteristics. This approach will enhance the design of RVO models and facilitate both basic and clinical research， which make it a scientifically valuable and necessary endeavor.

ObjectiveRetinal vein occlusion （RVO） is the second most common vascular disease leading to vision loss. Since its pathogenesis remains unclear， current Western medical treatments primarily target complications such as macular edema and neovascularization. The main therapeutic approaches include intravitreal injections of anti-vascular endothelial growth factor （VEGF） agents or corticosteroids， laser photocoagulation， and pars plana vitrectomy. However， these treatments cannot fully reverse disease progression or structural damage. Traditional Chinese medicine （TCM） has unique advantages in the clinical diagnosis and treatment of RVO， and integrated Chinese and Western medicine approaches may offer better clinical outcomes. This study， based on the clinical manifestations of RVO， systematically reviews the existing literature and evaluates the alignment of current RVO animal models with clinical manifestations. The aim is to identify the characteristics and limitations of existing models and provide recommendations and prospects for developing RVO animal models featuring the combination of disease and syndrome. MethodsDatabases including CNKI， Wanfang Data， PubMed， and Web of Science were searched with the keywords of "retinal vein occlusion" and "animal model". Model characteristics were assessed based on the diagnostic criteria for diseases and syndromes in both TCM and Western medicine. The alignment of each model with clinical manifestations was analyzed and evaluated. ResultsThe available RVO models were primarily established via methods such as laser photocoagulation， photodynamic therapy， diathermy， intravitreal drug injection， and mechanical modeling. These models demonstrated moderate overall alignment with clinical manifestations， mainly reflecting disease characteristics. However， they generally lack representation of TCM syndrome features. ConclusionExisting RVO models are predominantly based on Western medicine and lack TCM syndrome features. Western medical treatments for RVO have certain limitations， while syndrome differentiation and treatment in TCM offer potential advantages. Future research should focus on developing disease-syndrome integrated animal models that incorporate both pathological features and TCM syndrome characteristics. This approach will enhance the design of RVO models and facilitate both basic and clinical research， which make it a scientifically valuable and necessary endeavor.

Objective To explore the application value of dual-phase dual-energy CT (DECT) perfusion imaging in preoperative lung function assessment of lung cancer patients. Methods Data were collected from patients with stageⅠA non-small cell lung cancer who underwent surgical treatment in the Department of Thoracic Surgery, the First Affiliated Hospital of Nanjing Medical University, from November 2022 to June 2024. All patients underwent DECT perfusion imaging and pulmonary function testing (PFT) before surgery. PFT observation indicators included ventilation function indicators such as forced expiratory volume in one second (FEV1), forced vital capacity (FVC), 1-second rate (FEV1/FVC), maximal voluntary ventilation (MVV), and diffusion function indicators such as diffusing capacity for carbon monoxide (DLCO) and DLCO per liter of alveolar volume (DLCO/VA). The software eXamine was used to obtain quantitative parameters of DECT perfusion imaging, including volume parameters and perfusion parameters of both lungs and each lung lobe. The correlation between the volume parameters and perfusion parameters of both lungs and the ventilation and diffusion function indicators of the patients, as well as the differences in quantitative parameters of each lung lobe, was analyzed. Results The end-inspiration lung volume and biphasic volume difference were strongly positively correlated with FEV1 and FVC (r=0.636, r=0.682, r=0.614, r=0.624, P<0.001) and moderately positively correlated with MVV and DLCO (r=0.499, r=0.514, r=0.549, r=0.447, P<0.001); the end-expiration lung volume was weakly negatively correlated with DLCO/VA (r=−0.295, P=0.026); the volume ratio was positively correlated with FEV1, FVC, MVV, and MVV% (r=0.424, r=0.399, r=0.415, r=0.310, P<0.05); the end-inspiration iodine content was weakly positively correlated with DLCO/VA% (rs=0.292, P=0.030); the end-expiration iodine content was weakly positively correlated with FEV1, FVC, MVV, DLCO%, and DLCO/VA (r=0.307, r=0.299, r=0.295, r=0.366, r=0.320, P<0.05) and moderately positively correlated with DLCO (r=0.439, P<0.001); the end-inspiration iodine concentration was negatively correlated with FEV1, FVC, MVV, and MVV% (rs=−0.407, rs=−0.426, rs=−0.352, rs=−0.277, P＜0.05); the end-expiratory phase iodine concentration was moderately positively correlated with DLCO/VA (r=0.403, P=0.002); both the iodine concentration difference and the iodine concentration ratio were moderately positively correlated with FEV1, FEV1%, FVC, MVV, MVV% (P<0.05). The lung volume and iodine concentration ratio values were both highest in the left upper lung lobe and lowest in the right middle lung lobe; the differences in lung volume, lung volume ratio, intrapulmonary iodine content, and intrapulmonary iodine concentration were all highest in the lower lobes of both lungs and lowest in the middle lobe of the right lung. Conclusion Dual-phase DECT perfusion imaging can accurately assess overall lung function and quantify regional lung function.

Early caries confined to the enamel layer represent a critical window for achieving noninvasive intervention in caries management. Caries management has shifted from the traditional “drill-and-fill” model toward a modern paradigm centered on caries risk and lesion management. Based on contemporary concepts, this review systematically summarizes recent advances in early caries management, including caries risk assessment, early diagnosis, treatment strategy selection, and follow-up monitoring, while highlighting the major challenges currently being faced, and further reviewing and discussing the application of artificial intelligence (AI) in early caries management. In terms of risk management, conventional systems including the American Dental Association, Caries Management by Risk Assessment, Cariogram, and the Caries-Risk Assessment Tool remain mainstays in clinical practice. However, AI offers predictive capability through higher-dimensional data processing and the integration of numerous influencing factors, with the potential to improve the accuracy of risk stratification. For diagnosis, visual inspection, tactile examination, and bitewing radiography remain fundamental methods, yet their sensitivity for early caries—particularly proximal lesions—is limited. The application of optical technologies, including quantitative light-induced fluorescence, optical coherence tomography, near-infrared light transillumination, fiber-optic transillumination, and laser-induced fluorescence, enables digital characterization of caries lesions, providing a data foundation for demineralization assessment, lesion activity evaluation, and AI model development. The management of early caries primarily relies on noninvasive and minimally invasive approaches. Remineralization therapy is suitable for superficial lesions, resin infiltration offers the dual advantages of inhibiting lesion progression and improving aesthetics, and microabrasion and bleaching may serve as adjunctive aesthetic treatments. Emerging modalities such as laser, ozone, and photodynamic therapy have also demonstrated potential. Treatment decision-making should comprehensively consider lesion activity, patient caries risk status, demineralization depth, patient compliance, and treatment preferences. However, precise quantification of demineralization depth remains challenging, and standardized decision-making criteria are still lacking. Follow-up management should be individualized based on risk stratification, with attention to lesion changes, patient compliance, and the risk of recurrence. In summary, intelligent and precision-based approaches are expected to define the future of early caries management, and the application of AI in risk prediction, image analysis, and clinical decision support is anticipated to further enhance the efficiency and effectiveness of early caries diagnosis and treatment.

ObjectiveTo investigate the effect of repetitive peripheral magnetic stimulation (rPMS) combined with upper limb intelligent robotic training on muscle tension, motor function and cortical excitability in children with unilateral spastic cerebral palsy (USCP). MethodsFrom March, 2023 to December, 2024, 90 children with USCP admitted to Children's Hospital of Soochow University were selected and randomly divided into control group (n = 30), rPMS group (n = 30) and combined group (n = 30). The control group received conventional occupational therapy. The rPMS group received rPMS intervention followed by conventional occupational therapy. The combined group received rPMS followed by upper limb intelligent robot training, for four weeks. Before and after treatment, muscle tension of biceps brachii was assessed using the modified Ashworth Scale (MAS); upper limb motor function was evaluated using the Fugl-Meyer Assessment-Upper Extremity (FMA-UE) and upper limb intelligent parameters; and cortical excitability was measured using transcranial magnetic stimulation (TMS), including resting motor threshold (RMT) and motor-evoked potential (MEP) amplitude of the affected hemisphere. ResultsAfter treatment, MAS grades improved in all groups (|Z| > 3.523, P < 0.001), and the improvement in the combined group was superior to that in the control group (P < 0.05). Significant intra-group (F > 65.21, P < 0.001), inter-group (F > 17.94, P < 0.001) and interaction effects (F > 5.36, P < 0.01) were observed in FMA-UE scores, upper limb intelligent parameters and TMS parameters. Post Hoc analysis showed that the combined group demonstrated significantly greater improvements in FMA-UE scores, upper limb intelligent parameters, and TMS parameters compared with both the control and rPMS groups (all P < 0.01). Except for FMA-UE scores, the rPMS group showed significantly greater improvements than the control group in upper limb intelligent parameters (mechanical feedback, trajectory, and range of motion) and TMS parameters (RMT and MEP amplitude) (P < 0.05). ConclusionrPMS combined with upper limb intelligent robotic training can reduce upper limb muscle tension, improve motor function, and enhance cortical excitability in children with USCP.

Multidrug-resistant (MDR) bacterial infections have emerged as a serious challenge of global public health crisis. The overuse and misuse of conventional antibiotics have dramatically accelerated the emergence, evolution and worldwide spread of drug-resistant bacterial strains, necessitating urgent exploration of novel antibacterial strategies. Bacteriophages serve as natural bacterial predators offering distinct advantages including high host specificity, autonomous self-replication capabilities and cost-effective large-scale production. However, wild-type phages present significant clinical limitations due to their narrow host ranges, susceptibility to rapid immune clearance and poor penetration of bacterial biofilms, which severely restrict their therapeutic applications. The convergence of synthetic biology, nanotechnology and advanced gene editing technologies has accelerated the development of engineered bacteriophage platforms, providing programmable, scalable and clinically translatable pathways to overcome these inherent biological constraints. Here, we systematically delineate four fundamental strategies for engineered bacteriophage development. Chemical modification utilizes reactive functional groups such as amino, carboxyl and thiol moieties on capsid proteins through esterification, amidation or click chemistry reactions to achieve precise drug conjugation and surface functionalization. In vivo editing encompasses ultraviolet or chemical mutagenesis for random mutation induction, homologous recombination for targeted genetic alterations, recombineering methodologies including electroporation-mediated bacteriophage recombination engineering, and CRISPR-Cas systems for precise genome editing to enable exact genetic reconstruction and host range reprogramming. In vitro synthesis leverages genome engineering platforms where intact phage genomes are transferred into yeast or host bacteria to facilitate highly efficient homologous recombination, enabling large DNA fragment assembly and cross-gene host range expansion without bacterial toxicity constraints. Directed evolution combines artificial selection through mutation library screening with rational design approaches involving chimeric receptor binding protein construction or site-specific mutagenesis, effectively balancing the discovery of unknown adaptive pathways with targeted host specificity modification. Moreover, we comprehensively discuss therapeutic applications across diverse clinical scenarios. Engineered bacteriophage effectively disrupt bacterial biofilms through sophisticated functionalized delivery platforms including nanozyme-conjugated phages, phage-liposome nanoconjugates and bio-responsive hydrogels, demonstrating significantly enhanced bactericidal efficiency compared to unmodified free phages. These bioengineered vectors attenuate bacterial virulence and resensitize pathogens to antibiotics by delivering CRISPR-Cas systems or base editors to disrupt critical virulence factors such as pili, capsule synthesis machineries and quorum sensing systems, or by inactivating antibiotic resistance determinants including beta-lactamase genes. As an intelligent nanomedicine delivery platform, engineered bacteriophage enable precise pathogen elimination an through photocatalytic reactive oxygen species generation, immunomodulatory interventions, or controlled release of antibacterial drugs. Furthermore, oral administration of engineered bacteriophage facilitates microbiota modulation, which selectively eliminate intestinal pathogens while preserve beneficial commensal microbiota, thereby restoring microbial community balance and preventing complications associated with dysbiosis. Finally, we critically analyze persistent challenges including host strain matching complexity, evolution of bacterial resistance mechanisms, pharmacokinetic optimization requirements, optimal administration route selection, large-scale production quality control standards and clinical dosing determination protocols. Through multidisciplinary integration of synthetic biology, infectious disease medicine and immunology, future translational medicine studies of bacteriophage should establish comprehensive technical platforms encompassing rapid phage screening, intelligent rational design, rigorous in vivo evaluation and standardized clinical validation processes, ultimately advancing engineered bacteriophage from laboratory innovations to clinically approved therapeutics for effectively combating MDR bacterial infections.

Driven by policy initiatives promoting the integration of digital-intelligent technologies with primary healthcare and the digital transformation of traditional Chinese medicine (TCM), Smart TCM has emerged as a pivotal strategy for enhancing primary healthcare services for major chronic diseases. This paper reviews the current status, challenges, and feasible pathways of Smart TCM in community-level management of cardiovascular–cerebrovascular diseases and tumors, which represent major chronic disease burdens. Our findings indicate that Smart TCM demonstrates emerging potential in primary healthcare for chronic diseases across the entire continuum of “prevention-screening-diagnosis-treatment-management.” However, several significant challenges persist, including data silos and security vulnerabilities, limited applicability of existing models to real-world clinical needs, and insufficient digital literacy among primary healthcare physicians and elderly patients. To address these constraints, this paper proposes a multidimensional strategy encompassing the development of secure and interoperable regional data platforms, lightweight intelligent devices and support services aligned with primary care capacity, unified technical and data standards with corresponding quality control systems, adaptive and dynamically updated artificial intelligent models, interdisciplinary workforce training and patient education programs, and enhanced policy and health insurance support. Overall, Smart TCM shows great promise for improving the efficiency of primary healthcare delivery and establishing innovative TCM-based chronic disease management paradigms.

Objective: To explore the association role of anxiety and depressive symptoms with Internet gaming disorder (IGD) and emotional-behavioral problems among junior high school students, so as to provide references for preventing the occurrence and progression of emotional-behavioral problems in middle school students. Methods: From September to October 2024, a random cluster sampling method was adopted to select 38 069 students from 28 junior high schools in 14 counties (cities and districts) and functional areas of Jining City, Shandong Province. Surveys were conducted by Nine item Internet Gaming Disorder Scale-Short Form, Generalized Anxiety Disorder-7, Patient Health Questionnaire-9, and Strengths and Difficulties Questionnaire. The correlation of emotional and behavioral issues, online game addiction, anxiety and depressive symptoms among junior high school students was analyzed by Speaman correlation analysis. Mediation analysis was used to explore the role of anxiety and depressive symptoms between IGD and emotional-behavioral problems among junior high school students. Results: The detection rates of emotional-behavioral problems, anxiety symptoms, depressive symptoms, and IGD among junior high school students were 19.24 %, 9.48%, 16.69%, and 19.68%, respectively. The scores of emotional-behavioral problems, anxiety symptoms, depressive symptoms and IGD were 10.00 (6.00, 15.00), 3.00 (0.00, 7.00), and 4.00 (1.00, 8.00), 13.00 (10.00, 19.00), respectively. There were positive correlations between each pair of emotional-behavioral problem, IGD, anxiety symptoms, and depressive symptoms scores ( r =0.51-0.81, all P <0.01). Anxiety and depressive symptoms played mediating roles between IGD and emotional-behavioral problems among junior high school students, with mediating effect values of 0.16 (95% CI =0.15-0.17) and 0.12 (95% CI =0.11-0.14), respectively (both P <0.01). Conclusions Anxiety and depressive symptoms mediate the relationship between IGD and emotional-behavioral problems among junior high school students. It is necessary to identify early signs of IGD among junior high school students, strengthen intervention for anxiety and depressive symptoms, to prevent the occurrence and development of emotional and behavioral issues.

Objective To predict the lymph node metastasis status of patients with invasive pulmonary adenocarcinoma by constructing machine learning models based on primary tumor radiomics, peritumoral radiomics, and habitat radiomics, and to evaluate the predictive performance and generalization ability of different imaging features. Methods A retrospective analysis was performed on the clinical data of 1 263 patients with invasive pulmonary adenocarcinoma who underwent surgery at the Department of Thoracic Surgery, Jiangsu Province Hospital, from 2016 to 2019. Habitat regions were delineated by applying K-means clustering (average cluster number of 2) to the grayscale values of CT images. The peritumoral region was defined as a uniformly expanded area of 3 mm around the primary tumor. The primary tumor region was automatically segmented using V-net combined with manual correction and annotation. Subsequently, radiomics features were extracted based on these regions, and stacked machine learning models were constructed. Model performance was evaluated on the training, testing, and internal validation sets using the area under the receiver operating characteristic curve (AUC), F1 score, recall, and precision. Results After excluding patients who did not meet the screening criteria, a total of 651 patients were included. The training set consisted of 468 patients (181 males, 287 females) with an average age of (58.39±11.23) years, ranging from 29 to 78 years, the testing set included 140 patients (56 males, 84 females) with an average age of (58.81±10.70) years, ranging from 34 to 82 years, and the internal validation set comprised 43 patients (14 males, 29 females) with an average age of (60.16±10.68) years, ranging from 29 to 78 years. Although the habitat radiomics model did not show the optimal performance in the training set, it exhibited superior performance in the internal validation set, with an AUC of 0.952 [95%CI (0.87, 1.00)], an F1 score of 84.62%, and a precision-recall AUC of 0.892, outperforming the models based on the primary tumor and peritumoral regions. Conclusion The model constructed based on habitat radiomics demonstrated superior performance in the internal validation set, suggesting its potential for better generalization ability and clinical application in predicting lymph node metastasis status in pulmonary adenocarcinoma.

OBJECTIVE To improve the quality standard of Zhuang medicine Yingbupu （Aralia armata）. METHODS A total of 23 batches of Yingbupu （A. armata） were studied. Their macroscopic characteristics and powder microscopic features were observed. TLC was employed for the qualitative identification of oleanolic acid and araloside A. Items such as water content， total ash， acid-insoluble ash， and ethanol-soluble extract were determined according to the methods specified in the 2020 edition of the Chinese Pharmacopoeia （part Ⅳ）. UPLC fingerprint was established for 23 batches of samples by using Similarity Evaluation System for Chromatographic Fingerprints of Traditional Chinese Medicine （2012 edition）， and the contents of oleanolic acid and araloside A were determined. RESULTS The powder microscopic characteristics of the medicinal material were distinctive. Oleanolic acid and araloside A were detected by TLC in all 23 batches. Among the 23 batches of samples， the content ranges of moisture， total ash， acid-insoluble ash， and ethanol-soluble extract were 6.9% to 10.4%， 1.8% to 6.8%， 0.1% to 1.9%， and 2.8% to 8.4%， respectively. Based on the UPLC fingerprint， a total of 15 common peaks were obtained， and 9 of these common peaks were identified. The content ranges of oleanolic acid and araloside A in the 23 batches of samples were 0.86% to 2.69% and 0.16% to 1.10%， respectively. CONCLUSIONS This study has added items such as moisture and total ash content fingerprint， TLC identification. A preliminary quality standard has been established for the medicinal material of Yingbupu （A. armata）， stipulating that the moisture content should not exceed 11.0%， the total ash content should not exceed 5.0%， the acid-insoluble ash content should not exceed 2.5%， the ethanol-soluble extract（No. content should not be less than 4.0%， and the contents of zyyzdxk-2023165） oleanolic acid and araloside A should not be less than 1.00% and 0.45%（ calculated by a dried basis）， respectively.