ObjectiveAge-related macular degeneration （AMD） is one of the leading causes of low vision and blindness in people over 50 years old， and dry AMD （dAMD） is one type for which there is currently no clear treatment. On the basis of the diagnosis and clinical characteristics of dAMD in traditional Chinese and Western medicine， this paper evaluated the fitting degrees of existing animal models of dAMD with clinical characteristics according to the evaluation methods of animal models， and put forward suggestions and prospects. MethodsLiterature on animal models of dAMD was searched against database， and the characteristics of the models were assigned according to the diagnosis criteria of diseases and syndromes of traditional Chinese and Western medicine， and the fitting degrees of the models with clinical characteristics were analyzed and evaluated. ResultsAt present， the animal models of dAMD are mainly established targeting complement factors， chemokines， oxidative damage， lipid/glucose metabolism， and natural strains. Most of the models can simulate the major pathological changes of dAMD， showing the fitting degree of 25%-50% with clinical characteristics in Western medicine. However， the evaluation of traditional Chinese medicine （TCM） syndromes， especially the evaluation of secondary syndromes， is missing， and the models present low fitting degrees with the clinical characteristics in TCM. ConclusionExisting animal models of dAMD are mostly established under the guidance of Western diagnostic standards， which reproduce the main disease characteristics of Western medicine and lack observation of TCM syndromes. Future studies can pay attention to the intervention factors and evaluation systems of spleen deficiency Qi deficiency and liver-kidney Yin deficiency syndrome and build the animal model of dAMD with integration of disease and syndrome based on clinical characteristics of traditional Chinese and Western medicine.

ObjectiveAge-related macular degeneration （AMD） is one of the leading causes of low vision and blindness in people over 50 years old， and dry AMD （dAMD） is one type for which there is currently no clear treatment. On the basis of the diagnosis and clinical characteristics of dAMD in traditional Chinese and Western medicine， this paper evaluated the fitting degrees of existing animal models of dAMD with clinical characteristics according to the evaluation methods of animal models， and put forward suggestions and prospects. MethodsLiterature on animal models of dAMD was searched against database， and the characteristics of the models were assigned according to the diagnosis criteria of diseases and syndromes of traditional Chinese and Western medicine， and the fitting degrees of the models with clinical characteristics were analyzed and evaluated. ResultsAt present， the animal models of dAMD are mainly established targeting complement factors， chemokines， oxidative damage， lipid/glucose metabolism， and natural strains. Most of the models can simulate the major pathological changes of dAMD， showing the fitting degree of 25%-50% with clinical characteristics in Western medicine. However， the evaluation of traditional Chinese medicine （TCM） syndromes， especially the evaluation of secondary syndromes， is missing， and the models present low fitting degrees with the clinical characteristics in TCM. ConclusionExisting animal models of dAMD are mostly established under the guidance of Western diagnostic standards， which reproduce the main disease characteristics of Western medicine and lack observation of TCM syndromes. Future studies can pay attention to the intervention factors and evaluation systems of spleen deficiency Qi deficiency and liver-kidney Yin deficiency syndrome and build the animal model of dAMD with integration of disease and syndrome based on clinical characteristics of traditional Chinese and Western medicine.

Objective:To evaluate the value of ultrasound radiomics combined with machine learning for early diagnosis of seronegative Hashimoto’s thyroiditis (SN-HT) .Methods:This retrospective study included 164 patients from Liaoning Provincial People’s Hospital , Lixin County People’s Hospital, Linghai Dalinghe Hospital, Fengcheng Phoenix Hospital, who underwent thyroidectomy for solitary nodules with normal thyroid function between Nov. 2016 and Jan. 2024. Postoperative pathology confirmed Hashimoto’s thyroiditis (HT) in some cases, who were further categorized into antibody-positive and antibody-negative groups based on serum antibody status. Patients without Hashimoto’s thyroiditis served as the control group. A total of 298 ultrasound images were analyzed. Radiomics features were extracted from hypoechoic non-nodular areas within 0.5 cm surrounding the tumor. Two senior pathologists and two senior ultrasound physicians independently assessed lymphocytic infiltration, eosinophilic changes of follicular epithelium, and the proportion of hypoechoic areas in pathology and ultrasound images, respectively. A machine learning model, CCH-NET, was developed using linear regression and t-distributed stochastic neighbor embedding (t-SNE) techniques. The dataset was divided into a training set (80%) and a validation set (20%) to compare the diagnostic accuracy of CCH-NET with that of senior ultrasound physicians. Results:In internal validation, CCH-NET achieved a diagnostic accuracy of 88.89% for both antibody-positive and antibody-negative groups, significantly higher than the 66.67% accuracy of senior ultrasound physicians ( P<0.01). In external validation, CCH-NET achieved 75.00% and 66.67% accuracy for the two groups, compared to 50.00% by senior ultrasound physicians. For the control group, both methods achieved 93.33% accuracy. The AUC of CCH-NET was 0.848, outperforming senior ultrasound physicians (0.681) ,demonstrating superior diagnostic performance. Conclusion:The radiomics-based CCH-NET model, using non-nodular hypoechoic areas as a specific indicator, can accurately identify early SN-HT in euthyroid patients. It significantly outperforms senior ultrasound physicians, improving diagnostic accuracy and reducing missed diagnoses.

Objective To analyze the application trends and research hotspots of brain-computer interface(BCI)technology in stroke rehabilitation over the past five years.Methods Relevant literatures on the use of BCI in stroke rehabilitation published between January,2021 and August,2025 were retrieved from the Web of Science Core Collection database.CiteSpace 6.4.R1 was used for visualiza-tion analysis.Results A total of 458 papers were included.The annual number of publications remained at a high level.China was the leading country in publication output,with Fudan University and Aalborg University as the top institutions.The most prolific author was Mads R.Jochumsen,while G.Pfurtscheller had the highest citation frequency.The key-words and burst terms with the highest frequency in this field were brain-computer interface,motor imagery,up-per limb and deep learning.Conclusion Over the past five years,research on BCI in stroke rehabilitation has maintained a high publication volume.The research hotspots focus on innovations in BCI algorithm technology and multidimensional validation of neu-ral mechanisms and rehabilitation efficacy.

Currently,a wide range of oral antibacterial materials are clinically used,including metal element antibacterial materials(such as silver,zinc,copper,titanium),and non-metal element antibacterial materials(such as fluorine).In recent years,cerium ox-ide nanoparticles have attracted great interest in the field of oral medicine due to their unique antibacterial,anti-inflammatory,antioxi-dant,redox capabilities.At the same time,they also have the characteristics of promoting tissue regeneration,inhibiting biofilm forma-tion and good biocompatibility.To enhance the performance of oral materials,nanoparticles have been integrated into products such as composite resins,adhesives,and denture systems.Additionally,they have shown potential for modifying oral ceramic materials and an-ti-tumor effects.This review focuses on the latest research progress in various fields of oral medicine,including endodontics,periodon-tology,implantology,prosthodontics,and orthodontics,based on the biological characteristics of nano-cerium oxide.Our goal is to re-veal the potential of cerium oxide in the diagnosis and treatment of oral diseases and to provide ideas and references for the expansion of clinical applications in oral medicine.

Objective:To assess the professional knowledge proficiency of mainstream large language models (LLMs) in medical laboratory education and to explore their potential as educational aids for medical laboratory technology students.Methods:A comprehensive evaluation was conducted using 400 authentic questions from the 2023 Chinese National Clinical Medical Laboratory Technician Qualification Examination. Five LLMs (Copilot, Grok, Yuanbao, Doubao, and Kimi) were tested through two-round interactions using zero-shot prompting and interaction-optimized prompting strategies. The accuracy of answers and the quality of generated content were evaluated. Performance disparities were analyzed using Cochran's Q test. Content quality was scored through the CLEAR framework (completeness, lack of false information, evidence-based reasoning, appropriateness, relevance).Results:In the first-round test, Doubao achieved the highest overall accuracy rate (375/400). The overall accuracy rates of Doubao and Yuanbao significantly outperformed Copilot and Kimi ( P<0.001). After the second-round interactive optimization, the accuracy rate of Kimi significantly improved ( P<0.05), whereas other LLMs showed slight improvements ( P>0.05). Doubao still had the highest overall accuracy rate (380/400). The overall accuracy rates of Doubao and Yuanbao significantly outperformed Copilot ( P<0.005). Evaluation based on the CLEAR framework revealed that Yuanbao, Doubao, and Kimi significantly outperformed foreign models in the dimensions of evidence-based reasoning ( P<0.003) and completeness ( P<0.05), demonstrating standardized citation of authoritative evidence and superior content quality. Conclusions:The tested LLMs possess extensive medical laboratory knowledge. The accuracy of their answers and the quality of the generated content can be improved through single-question input, specifying evidence requirements, and enabling advanced reasoning functions. Domestic LLMs are comparable to foreign LLMs in terms of accuracy, and have significant advantages in the dimensions of evidence-based reasoning and completeness. LLMs can serve as auxiliary tools for learning professional knowledge in medical laboratory technology.

Objective:To explore the relationships between physical activity and cognitive impairment in older adults aged ≥65 years in longevity areas in China.Methods:A total of 6 081 older adults aged ≥65 years from the Healthy Ageing and Biomarkers Cohort Study in China in 2021 were included in this study. Information about their demographic characteristics, lifestyles, and chronic disease histories were collected, the intensity of physical activity was evaluated by using Physical Activity Scale for the Elderly, and the cognitive function was evaluated by using Mini-Mental State Examination Scale (Chinese version). Multifactorial logistic regression model was used to analyze the associations between different levels and types of physical activity and cognitive impairment in older adults.Results:In the 6 081 older adults, 1 829 (30.1%) had cognitive impairment. After adjusting for confounders, older adults with T2 and T3 levels of physical activity had lower risks for cognitive impairment compared with those with T1 levels of physical activity, with ORs of 0.47 (95% CI: 0.40-0.55) and 0.22 (95% CI: 0.18-0.28). The results of different types of physical activities showed that the ORs in leisure activity T2 and T3 groups were 0.52 (95% CI: 0.44-0.63) and 0.49 (95% CI: 0.41-0.58), and the ORs in housework activity T2 and T3 groups were 0.36 (95% CI: 0.30-0.42) and 0.19 (95% CI: 0.16-0.24). There was no significant association between work-related activity and cognitive impairment. Conclusion:There is a negative association between the intensity level of physical activity and cognitive impairment, and active leisure and household activities might reduce the risk for cognitive impairment.

Objective:To explore the relationships between physical activity and cognitive impairment in older adults aged ≥65 years in longevity areas in China.Methods:A total of 6 081 older adults aged ≥65 years from the Healthy Ageing and Biomarkers Cohort Study in China in 2021 were included in this study. Information about their demographic characteristics, lifestyles, and chronic disease histories were collected, the intensity of physical activity was evaluated by using Physical Activity Scale for the Elderly, and the cognitive function was evaluated by using Mini-Mental State Examination Scale (Chinese version). Multifactorial logistic regression model was used to analyze the associations between different levels and types of physical activity and cognitive impairment in older adults.Results:In the 6 081 older adults, 1 829 (30.1%) had cognitive impairment. After adjusting for confounders, older adults with T2 and T3 levels of physical activity had lower risks for cognitive impairment compared with those with T1 levels of physical activity, with ORs of 0.47 (95% CI: 0.40-0.55) and 0.22 (95% CI: 0.18-0.28). The results of different types of physical activities showed that the ORs in leisure activity T2 and T3 groups were 0.52 (95% CI: 0.44-0.63) and 0.49 (95% CI: 0.41-0.58), and the ORs in housework activity T2 and T3 groups were 0.36 (95% CI: 0.30-0.42) and 0.19 (95% CI: 0.16-0.24). There was no significant association between work-related activity and cognitive impairment. Conclusion:There is a negative association between the intensity level of physical activity and cognitive impairment, and active leisure and household activities might reduce the risk for cognitive impairment.

AIM:To establish an optimal protocol for isolating and extracting mouse hepatocellular carcinoma H22 cell-detrived microparticles(H22-MPs),evaluate their stimulating effect on dendritic cells(DC),and investigate the cytotoxic capacity of CD8+T cells induced by H22-MPs on hepatocellular carcinoma cells.METHODS:The H22-MPs were extracted by high-speed differential centrifugation,and the morphology of H22-MPs was observed by transmis-sion electron microscopy.The particle size distribution of H22-MPs was detected by dynamic light scattering,and the ex-pression of vesicle surface markers was detected by Western blot.The protein components and pathways involved by MPs were analyzed by labeling free quantitative proteomics combining with bioinformatics GO and KEGG enrichment methods.The effect of MPs antigen on the expression of CD11c,a mature marker of DC,was detected by laser confocal microscopy.Next,CD8+T cells were sorted by magnetic beads,and the secretion of tumor necrosis factor-α(TNF-α),interferon-γ(IFN-γ)and interleukin-2(IL-2)in the supernatant of CD8+T cells stimulated by DC loaded with H22-MPs was detected by ELISA.Lactate dehydrogenase(LDH)test was conducted to evaluate the specific killing effect of CD8+T cells induced by DC loaded with H22-MPs on hepatocellular carcinoma cells.RESULTS:The results showed that the morphology,size and vesicle markers of H22-MPs met the requirements.Most of the H22-MPs protein antigens were derived from its parent cell H22 and coordinated various signal transduction pathways in the cells.Subsequently,it was detected that H22-MPs increased the expression of CD11c on the surface of DC,and H22-MPs were mainly localized in the lysosomes of DC.In addition,DC loaded with H22-MPs stimulated CD8+T to release high levels of TNF-α,IFN-γ and IL-2,and it also pro-moted CD8+T to overexpress CD69,thus inducing CD8+T to killhepatocellular carcinoma cells specifically.CONCLU-SION:H22-MPs promote the maturation of DC,and the mature DC may induce CD8+T cells to play an anti-hepatocellu-lar carcinoma immune response by promoting the activation of CD8+T cells.

Breast cancer is the leading cause of cancer-related mortality among women worldwide and has drawn extensive research attention.Owing to its molecular heterogeneity,drug resistance,and low therapeutic response,single-modality treatments often fail to achieve satisfactory efficacy or broad applicability.Combination therapy,designed based on the pathophysiological characteristics,related signaling pathways,and biomarkers of breast cancer,has emerged as a promising approach for improving therapeutic outcomes.With the advancement of research on combination strategies,the understanding of their molecular mechanisms—particularly key signaling pathways and biomarkers—has become increasingly important.However,comprehensive reviews addressing these molecular mechanisms and synergistic strategies remain scarce.This article summarizes recent advances in combination therapy for breast cancer,providing a comprehensive review of recent combination therapies for breast cancer and their underlying molecular mechanisms,and focusing on key signaling pathways involved in combination therapy and synergistic strategies,thereby providing theoretical insights and reference for researchers,graduate students,and clinicians engaged in the development of novel combination therapeutic strategies for breast cancer and related malignancies.