With the rapid advancement of artificial intelligence technology, chatbots have shown great potential in the healthcare sector. From personalized health advice to chronic disease management and psychological support, chatbots have demonstrated significant advantages in improving the efficiency and quality of healthcare services. As the scope of their applications expands, the relationship between technological complexity and practical application scenarios has become increasingly intertwined, necessitating a more comprehensive evaluation of both aspects. This paper, from the perspective of he althcare applications, systematically reviews the technological pathways and development of chatbots in the medical field, providing an in-depth analysis of their performance across various medical scenarios. It thoroughly examines the advantages and limitations of chatbots, aiming to offer theoretical support for future research and propose feasible recommendations for the broader adoption of chatbot technologies in healthcare.

Objective:To investigate the effect of polystyrene microplastics(PS-MPs)combined with high-fat treatment on vascular endothelial cells.Methods:Human umbilical vein endothelial cells(HUVECs)were cultured in the DMEM medium containing 5%fe-tal bovine serum.HUVECs were treated with conventional culture,high-fat treatment,and PS-MPs combined with high-fat treatment.The experiment was conducted in the three groups of control group,high-fat treatment group and PS-MPs+high-fat treatment group.CCK-8 assay was used to measure cell viability,F-actin staining was used to observe cell morphological changes,and flow cytometry,scratch assay,and tube formation assay were used to measure the apoptosis,migration,and tube-forming ability of cells.Results:After HUVECs were exposed to the high-fat environment,there was a significant reduction in cell viability,shrinkage of cells,a signifi-cant increase in cell apoptosis,and significant reductions in cell migration and tube-forming ability.Compared with the high-fat treat-ment group,there were no significant changes in cell viability,cell morphology,cell apoptosis,and cell migration ability after PS-MPs combined with high-fat treatment,but the tube-forming ability of cells was further impaired.Conclusion:High-fat treatment will affect cell viability,change cell morphology,and damage vascular endothelial cell function,and PS-MPs combined with high-fat treat-ment can aggravate the damage of vascular endothelial cell function.

Objective To develop and compare prediction models for hyperuricemia(HUA)in perim-enopausal and postmenopausal women using Lasso regression,random forest,and multivariate logistic regres-sion.Methods A multi-stage,stratified cluster sampling method was used to select 12 790 subjects from An-ning City,Yunnan Province.Prediction models for HUA were constructed using Lasso regression,random for-est,and multivariate logistic regression.The efficacy of the model was evaluated by accuracy,sensitivity,speci-ficity,F1 score,and area under the curve(AUC).Results LASSO regression analysis screened 19 variables for inclusion in the model,such as age,waist circumference,diastolic blood pressure,BMI,HDL-C,fasting blood glucose(FBG),etc.The accuracy rate was 0.701,the sensitivity was 0.703,the specificity was 0.680,and the F1 score was 0.806.The AUC(95%CI)was 0.770(0.748-0.792).The results of the random forest model show that variables such as creatinine,triglyceride-glucose index(TyG),TG,BMI,TC,Urea nitrogen(Urea),and ALT were relatively important,with an accuracy rate of 0.663,a sensitivity of 0.653,a specificity of 0.738,and an F1 score of 0.774.The AUC(95%CI)was 0.763(0.741-0.785).Multivariate logistic re-gression results showed that 11 variables including creatinine(Cr),TyG,BMI,Urea,and ALT were included in the model,with an accuracy rate of 0.705,a sensitivity of 0.707,a specificity of 0.686,an F1 score of 0.809,and an AUC(95%CI)of 0.771(0.749-0.793).Conclusion The overall performance of LASSO re-gression and multivariate logistic regression models is better.The random forest model has a strong variable screening ability and high specificity,and can be used as a supplement to provide more accurate predictions.

The translation of genetic findings from genome-wide association studies into actionable therapeutics persists as a critical challenge in Alzheimer's disease (AD) research. Here, we present PI4AD, a computational medicine framework that integrates multi-omics data, systems biology, and artificial neural networks for therapeutic discovery. This framework leverages multi-omic and network evidence to deliver three core functionalities: clinical target prioritisation; self-organising prioritisation map construction, distinguishing AD-specific targets from those linked to neuropsychiatric disorders; and pathway crosstalk-informed therapeutic discovery. PI4AD successfully recovers clinically validated targets like APP and ESR1, confirming its prioritisation efficacy. Its artificial neural network component identifies disease-specific molecular signatures, while pathway crosstalk analysis reveals critical nodal genes (e.g., HRAS and MAPK1), drug repurposing candidates, and clinically relevant network modules. By validating targets, elucidating disease-specific therapeutic potentials, and exploring crosstalk mechanisms, PI4AD bridges genetic insights with pathway-level biology, establishing a systems genetics foundation for rational therapeutic development. Importantly, its emphasis on Ras-centred pathways-implicated in synaptic dysfunction and neuroinflammation-provides a strategy to disrupt AD progression, complementing conventional amyloid/tau-focused paradigms, with the future potential to redefine treatment strategies in conjunction with mRNA therapeutics and thereby advance translational medicine in neurodegeneration.

In recent years, the prevalence of myopia has shown a significant upward trend characterized by earlier onset and accelerated progression rates. This epidemic not only imposes an increasing socioeconomic burden but also leads to severe vision impairment through high myopia-related complications that profoundly affect daily life. Current research on the pathogenesis of myopia primarily focuses on four mechanistic theories, including scleral remodeling, choroidal hemodynamic abnormalities, dopamine synthesis and metabolism, and inflammatory responses. The advent of high-throughput sequencing technologies has revolutionized our investigative approaches, enabling deeper exploration into myopia development through multi-omics strategies encompassing genomics, proteomics, and metabolomics. These cutting-edge methodologies have provided novel insights for myopia prevention and control, while simultaneously identifying potential therapeutic targets for precision intervention. This review focuses on summarizing the aforementioned research findings.

Heart and spleen deficiency syndrome is the most common syndrome type in patients with insomnia. Based on the theory of disease syndrome-combined animal model， this paper used multiple databases to search for the keywords "heart and spleen deficiency"， "insomnia"， "sleepless"， "disease syndrome-combined animal model"， "model evaluation"， etc. It selected the literature related to the animal model of insomnia with heart and spleen deficiency in the past 20 years to evaluate from the aspects of model establishment， modeling factors， syndrome model， disease model， macro characterization & macro characterization evaluation scale， micro indicators， etc. It is found that the existing animal model of insomnia with heart and spleen deficiency is not completely constructed by the method of disease syndrome combination of disease modeling factors and syndrome modeling factors. In the model using this method， the single establishment factor of heart and spleen deficiency does not conform to the clinical reality of disease， and the selection of the factors for the insomnia model is not closely related to or even separated from the syndrome performance. There is a problem of insufficient quantification of macro representation when the macro representation of the model replaces the symptoms related to heart and spleen deficiency syndrome and insomnia in an equivalent manner for macro representation evaluation， which can be improved according to the quantitative ideas and examples of the existing macro representation and macro representation evaluation scale. There are few specific indicators of heart and spleen deficiency syndrome in micro indicators. The micro research of heart and spleen deficiency syndrome and the essence of other traditional Chinese medicine （TCM） syndromes can be carried out by metabonomics and other technologies combined with the theory of corresponding prescription and syndrome， along the specific related ideas of "prescription and syndrome， treatment principle and selection of prescription， treatment principle and selection of acupoints， as well as therapeutic mechanism and syndrome essence". The future users and researchers of animal models of insomnia with heart and spleen deficiency can get improved methods and ideas through the shortcomings of animal models of heart and spleen deficiency listed in this paper and construct animal models of insomnia with heart and spleen deficiency that are more suitable for clinical practice， so as to establish a more perfect modeling method and evaluation system of disease syndrome-combined animal model.