Chronic obstructive pulmonary disease （COPD）， as one of the three major causes of death， is a complex systemic disease with high prevalence， high mortality， high disability， frequent acute exacerbations， and a variety of pulmonary complications. The pathogenesis is complex. Western medicine has no effective specificity scheme for a complete cure. However， multiple-component and multiple-target characteristics of traditional Chinese medicine （TCM） demonstrate significant advantages in COPD treatment through multi-link， multi-pathway， and multi-mechanism intervention. Therefore， exploring the essence of COPD pathogenesis and discovering effective TCM treatment drugs through the application of TCM principles and prescriptions is a key focus of modern research. Animal models are of paramount importance in medical research. It is the first consideration to select appropriate animals， adopt reasonable modeling methods to replicate stable animal models that closely resemble the clinical manifestations and pathophysiological characteristics of COPD， and use appropriate evaluation methods to determine the success of COPD animal models in experimental research. The core of experimental research lies in observing the intervention effect of TCM on COPD animal models， exploring the specific pathways and regulatory mechanisms of TCM on COPD disease， and finding TCM monomers， single herbs， and TCM formulas with definite curative effects. At present， animal model research on COPD mainly involves model establishment， model evaluation， efficacy observation， mechanism exploration， and other aspects. In recent years， there has been no systematic organization， update， and reflection on the relevant research on TCM intervention in COPD animal models. This study reviewed the selection of animals for the COPD model， methods for establishing COPD animal models， model evaluation methods， and the intervention effects of TCM on COPD animal models. It aims to grasp the current research status and identify existing problems for further improvement， in order to provide evidence and support for scientific research and clinical treatment of COPD.

Chronic obstructive pulmonary disease （COPD）， as one of the three major causes of death， is a complex systemic disease with high prevalence， high mortality， high disability， frequent acute exacerbations， and a variety of pulmonary complications. The pathogenesis is complex. Western medicine has no effective specificity scheme for a complete cure. However， multiple-component and multiple-target characteristics of traditional Chinese medicine （TCM） demonstrate significant advantages in COPD treatment through multi-link， multi-pathway， and multi-mechanism intervention. Therefore， exploring the essence of COPD pathogenesis and discovering effective TCM treatment drugs through the application of TCM principles and prescriptions is a key focus of modern research. Animal models are of paramount importance in medical research. It is the first consideration to select appropriate animals， adopt reasonable modeling methods to replicate stable animal models that closely resemble the clinical manifestations and pathophysiological characteristics of COPD， and use appropriate evaluation methods to determine the success of COPD animal models in experimental research. The core of experimental research lies in observing the intervention effect of TCM on COPD animal models， exploring the specific pathways and regulatory mechanisms of TCM on COPD disease， and finding TCM monomers， single herbs， and TCM formulas with definite curative effects. At present， animal model research on COPD mainly involves model establishment， model evaluation， efficacy observation， mechanism exploration， and other aspects. In recent years， there has been no systematic organization， update， and reflection on the relevant research on TCM intervention in COPD animal models. This study reviewed the selection of animals for the COPD model， methods for establishing COPD animal models， model evaluation methods， and the intervention effects of TCM on COPD animal models. It aims to grasp the current research status and identify existing problems for further improvement， in order to provide evidence and support for scientific research and clinical treatment of COPD.

ObjectiveThis paper aims to find the identified and validated clinical biomarker data building upon a clinical study of early-phase phase Ⅱ and investigate the correlation analysis of Huanglian Jiedu Wan on syndrome improvement and clinical biomarkers in the treatment of "excess heat-toxicity" based on a machine learning model. Additionally， the effective prediction of clinical biomarker values for the main symptoms of the "excess heat-toxicity" syndrome was assessed. MethodsA total of 229 patients meeting the inclusion criteria for "excess heat-toxicity" syndrome were randomly divided into the Huanglian Jiedu Wan group and the placebo group. Syndrome score transition matrices were constructed for the Huanglian Jiedu Wan group and the placebo group based on three main symptoms of "excess heat-toxicity" syndrome， such as oral ulcers， sore throat， and gum swelling and pain. Data from the patients with these three syndromes were also integrated for an overall analysis. The corresponding syndrome score transition matrices were further constructed to visualize symptom change trends of the patients in the two groups via heatmaps. Based on the identified and validated clinical biomarkers related to inflammation， oxidative stress， and energy metabolism in the early phase， Spearman correlation analysis was employed to analyze and evaluate the associations between clinical biomarkers and syndrome improvement. Key clinical biomarkers reflecting the effect of Huanglian Jiedu Wan were screened through the comparison of differences between groups. An extreme gradient boosting （XGBoost） algorithm was used to develop a prediction model for main symptom classification， with classification performance evaluated through 10-fold cross-validation. Feature importance analysis was applied to identify variables with the greatest contribution to the prediction result. ResultsThe syndrome transition matrix results indicated that the Huanglian Jiedu Wan group showed a superior effect to the placebo group in improving oral ulcers， sore throat， and overall symptoms， with significant effects observed especially in sore throat and overall symptom analyses （P<0.01）. Spearman correlation analysis revealed that several clinical biomarkers positively correlated with "excess heat-toxicity" syndrome and its main symptom improvement， were also called "heat-related biomarkers"， including succinic acid， α-ketoglutaric acid， glycine， lactic acid， adenosine monophosphate （AMP）， tumor necrosis factor-α （TNF-α）， interferon-γ （IFN-γ）， interleukin-1β （IL-1β）， interleukin-4 （IL-4）， interleukin-6 （IL-6）， interleukin-8 （IL-8）， interleukin-10 （IL-10）， and so on. Conversely， clinical biomarkers negatively correlated with symptom severity， were also called "heat-clearing related biomarkers" after administration of Huanglian Jiedu Wan， including malic acid， fumaric acid， cis-aconitic acid， adrenocorticotropic hormone （ACTH）， IL-1β， IL-4， IL-8， succinic acid， and citric acid. The XGBoost classification model using all 52 biomarkers as variables achieved an average test accuracy of 0.754 and an average F1 score of 0.777. Feature importance analysis identified the scores of glutamic acid in saliva and IL-6 were the highest in all the variables， with importance scores of 0.081 and 0.080， respectively. After screening out 14 key variables and optimizing the parameters， model performance improved to an average accuracy of 0.758 and an F1 score of 0.798. Feature importance analysis further determined that the glutamic acid in saliva and IL-6 showed obvious changes after screening the variables， confirming the good syndrome prediction ability of the model constructed by these key clinical biomarkers. ConclusionThis study systematically elucidates the correlation between syndrome improvement and clinical biomarkers of Huanglian Jiedu Wan in the treatment of "excess heat-toxicity" syndrome. An XGBoost classification model based on key clinical biomarkers is successfully established， achieving effective prediction of the symptoms related to the "excess heat-toxicity" syndrome such as oral ulcers and sore throat and providing a new insight for objective identification of traditional Chinese medicine syndromes.

ObjectiveThis paper aims to find the identified and validated clinical biomarker data building upon a clinical study of early-phase phase Ⅱ and investigate the correlation analysis of Huanglian Jiedu Wan on syndrome improvement and clinical biomarkers in the treatment of "excess heat-toxicity" based on a machine learning model. Additionally， the effective prediction of clinical biomarker values for the main symptoms of the "excess heat-toxicity" syndrome was assessed. MethodsA total of 229 patients meeting the inclusion criteria for "excess heat-toxicity" syndrome were randomly divided into the Huanglian Jiedu Wan group and the placebo group. Syndrome score transition matrices were constructed for the Huanglian Jiedu Wan group and the placebo group based on three main symptoms of "excess heat-toxicity" syndrome， such as oral ulcers， sore throat， and gum swelling and pain. Data from the patients with these three syndromes were also integrated for an overall analysis. The corresponding syndrome score transition matrices were further constructed to visualize symptom change trends of the patients in the two groups via heatmaps. Based on the identified and validated clinical biomarkers related to inflammation， oxidative stress， and energy metabolism in the early phase， Spearman correlation analysis was employed to analyze and evaluate the associations between clinical biomarkers and syndrome improvement. Key clinical biomarkers reflecting the effect of Huanglian Jiedu Wan were screened through the comparison of differences between groups. An extreme gradient boosting （XGBoost） algorithm was used to develop a prediction model for main symptom classification， with classification performance evaluated through 10-fold cross-validation. Feature importance analysis was applied to identify variables with the greatest contribution to the prediction result. ResultsThe syndrome transition matrix results indicated that the Huanglian Jiedu Wan group showed a superior effect to the placebo group in improving oral ulcers， sore throat， and overall symptoms， with significant effects observed especially in sore throat and overall symptom analyses （P<0.01）. Spearman correlation analysis revealed that several clinical biomarkers positively correlated with "excess heat-toxicity" syndrome and its main symptom improvement， were also called "heat-related biomarkers"， including succinic acid， α-ketoglutaric acid， glycine， lactic acid， adenosine monophosphate （AMP）， tumor necrosis factor-α （TNF-α）， interferon-γ （IFN-γ）， interleukin-1β （IL-1β）， interleukin-4 （IL-4）， interleukin-6 （IL-6）， interleukin-8 （IL-8）， interleukin-10 （IL-10）， and so on. Conversely， clinical biomarkers negatively correlated with symptom severity， were also called "heat-clearing related biomarkers" after administration of Huanglian Jiedu Wan， including malic acid， fumaric acid， cis-aconitic acid， adrenocorticotropic hormone （ACTH）， IL-1β， IL-4， IL-8， succinic acid， and citric acid. The XGBoost classification model using all 52 biomarkers as variables achieved an average test accuracy of 0.754 and an average F1 score of 0.777. Feature importance analysis identified the scores of glutamic acid in saliva and IL-6 were the highest in all the variables， with importance scores of 0.081 and 0.080， respectively. After screening out 14 key variables and optimizing the parameters， model performance improved to an average accuracy of 0.758 and an F1 score of 0.798. Feature importance analysis further determined that the glutamic acid in saliva and IL-6 showed obvious changes after screening the variables， confirming the good syndrome prediction ability of the model constructed by these key clinical biomarkers. ConclusionThis study systematically elucidates the correlation between syndrome improvement and clinical biomarkers of Huanglian Jiedu Wan in the treatment of "excess heat-toxicity" syndrome. An XGBoost classification model based on key clinical biomarkers is successfully established， achieving effective prediction of the symptoms related to the "excess heat-toxicity" syndrome such as oral ulcers and sore throat and providing a new insight for objective identification of traditional Chinese medicine syndromes.

Plant-derived exosome-like nanovesicles (PELNs), characterized by a natural lipid bilayer membrane, have rapidly emerged as a prominent research frontier in medicine owing to their unique biological properties and robust therapeutic potential. This review comprehensively examines the biological profiles, mechanistic functions, and recent engineering advancements of PELNs. In terms of composition, PELNs are uniquely enriched in plant-specific glycolipids, phosphatidylserine, secondary metabolites, and highly stable 2'-O-methylated miRNAs. This distinct molecular makeup endows them with exceptional biocompatibility, negligible immunogenicity, and the capacity for cross-species molecular communication. Mechanistically, PELNs demonstrate profound anti-inflammatory efficacy by suppressing the NF-κB and NLRP3 inflammasome pathways. They also serve as potent immune modulators, driving macrophage M1/M2 polarization and regulating T cell activity. Additionally, PELNs exhibit promising antitumor capabilities, targeting malignancies via reactive oxygen species (ROS) induction, TRAIL pathway activation, and tumor microenvironment remodeling. Crucially, the plant miRNAs encapsulated within PELNs remain highly stable in the gastrointestinal tract, allowing them to selectively alter gene expression in specific gut microbiota communities. This interaction deeply influences host immunity and metabolism, highlighting the vital role in cross-species regulation. Advancements in bioengineering have further expanded the clinical utility of PELNs. Targeted delivery efficiency can be significantly amplified via surface functionalization (e.g., folate and RGD sequences) and state-of-the-art drug loading technologies such as sonication and electroporation. Consequently, engineered PELNs surpass traditional synthetic nanocarriers in penetrating natural physiological barriers, particularly for oral and transdermal drug administration. Despite these advantages, clinical translation is currently hindered by the lack of standardized isolation protocols, challenges in scalable manufacturing, and the need for robust quality control frameworks. Looking forward, the integration of multi-omics approaches and AI-driven “molecular fingerprinting”—coupled with the design of synthetic biomimetic vesicles—will be instrumental in overcoming these bottlenecks, ultimately establishing PELNs as a next-generation platform for precision medicine and targeted nanotherapeutic delivery.

Objective To understand mosquito density, species composition, and seasonal variations around the Beijing Capital International Airport(BCIA)and provide scientific evidence for mosquito-borne disease prevention and control. Methods Meteorological data were collected from 2016 to 2022, and mosquito density was monitored at seven surveillance sites around the BCIA from May to October each year using CO2-baited mosquito traps to analyze the relationship between mosquito density and meteorological factors. Results In total,68 518 female mosquitoes were captured, with a mosquito density of 10.20 per light · hour. The dominant species was Culex pipiens pallens(73.90%), followed by Aedes albopictus(9.71%)and Ae. vexans(9.29%);the mosquito density was highest in 2016(14.8 per light·hour)and lowest in 2022(4.46 per light·hour). Significant statistical differences were observed in mosquito density among different species(F=18.118, P<0.05). The density of Cx. pipiens pallens and other mosquito species showed a mutually exclusive trend; the peak of mosquito density varied based on years and habitats, with significant statistical differences in mosquito density among different habitats(F=8.504, P<0.05). The highest mosquito density was observed near the Wenyu River(21.50 per light·hour), whereas the lowest was recorded at the BCIA construction site(2.44 per light· hour). The monthly average temperature(r=0.595), monthly average highest temperature(r=0.575), and monthly average lowest temperature(r=0.624)showed moderate positive correlations, whereas the monthly average air pressure(r=-0.484)showed a moderate negative correlation. The monthly average minimum temperature was included in the regression model(F=25.575, P<0.000), and the equation Y=1.029X4-8.181 was used. The monthly average air pressure 2 months prior(b=-2.418, β=-1.619, P<0.05)and the monthly average relative humidity(b=-0.739, β=-1.201, P<0.05)significantly negatively predicted the mosquito density. Notably, the regression equation used was y=2526.170+(-2.418)X9+(-0.739)X13. The exposure-response analysis revealed that the density of mosquitoes was not linearly related to the average monthly air pressure, rainfall, and duration of sunshine. Conclusions The dominant mosquito species around the BCIA was Cx. pipiens pallens, Ae. albopictus, and Ae. vexans. During the control of Cx. pipiens pallens, the impact on other mosquito species must also be considered. Environmental management, breeding sites, and scientific use of pesticides should be prioritized based on the activity periods of mosquitoes. Further studies on mosquitoes and meteorological factors should be conducted to provide references and novel avenues for mosquito control.

Purpose To explore the characteristics of left and right ventricular myocardial strain in hypertensive heart disease(HHD)assessed by magnetic resonance feature tracking technique,and to assess the effect of HHD on right ventricular function.Materials and Methods A retrospective analysis was performed on 40 patients with HHD at the General Hospital of Ningxia Medical University from January 2022 to August 2023.Among these 40 HHD patients,19 presented with a left ventricular ejection fraction(LVEF)of≥50%,and 21 presented with an LVEF of<50%.Additionally,25 healthy controls were enrolled.All subjects underwent cardiac magnetic resonance imaging.The cine sequence images were imported into cardiac post-processing analysis software(QIR suite software).The left ventricular radial strain(LVRS),left ventricular circumferential strain(LVCS),left ventricular longitudinal strain(LVLS)and right ventricular longitudinal strain(RVLS)were measured,and left and right ventricular strain parameters of the three groups were analyzed statistically.Results The absolute values of LVRS,LVCS,LVLS and RVLS in the HHD group with LVEF<50%were lower than those in the normal control group(t=7.48,-12.69,-8.19,-6.32,all P<0.001)and those in the HHD group with LVEF≥50%(t=5.97,-8.88,-4.50,-4.90,all P<0.001);the area under the curve values of LVRS,LVCS,LVLS and RVLS for distinguishing HHD from normal controls were 0.804,0.785,0.829,0.832,respectively,and the cut-off values of LVRS,LVCS,LVLS and RVLS were 22.9%,-10.0%,-11.9%and-18.7%,respectively.Conclusion Magnetic resonance feature tracking technique can detect left and right ventricular myocardial dysfunction in HHD at an early stage and can provide a new basis for evaluating cardiac function.

Objective To investigate the clinical effects and safety of dual mobility total hip arthroplasty for the treatment of femoral neck fracture of the hemiplegic side.Methods Patients with hemiplegia and femoral neck fracture who underwent hip arthroplasty in our hospital from March 2021 to March 2023 were selected as the research objects,and they were randomly divided into the dual mobility group(dual mobility total hip arthroplasty was performed)and the hemiarthroplasty group(hemiarthroplasty was performed),with 31 cases in each group.The perioperative status,postoperative hip function and postoperative complications of patients in the two groups were analyzed and compared.Results The operative time of patients in the dual mobility group was longer than that in the hemiarthroplasty group,the difference was statistically significant(P<0.05),but there was no statistically significant difference in intraoperative blood loss,total drainage volume 3 days after operation or hospital stay between the two groups(P>0.05).One month after surgery,there was no significant difference in hip Harris score between the two groups(P>0.05).At 6 months and 12 months after surgery,the hip Harris scores of patients in the dual mobility group were better than those in the hemiarthroplasty group,and the differences were statistically significant(P<0.05).In the case of different preoperative muscle strength of the hemiplegic side,the hip Harris scores of patients in the dual mobility group at 6 months and 12 months after surgery were better than those in the hemiarthroplasty group,and the differences were statistically significant(P<0.05).The incidence of postoperative complications was 12.9%(4/31)in the dual mobility group,and it was 22.6%(7/31)in the hemiarthroplasty group,without significant difference between the two groups(P>0.05).Conclusion For patients with femoral neck fracture and decreased muscle strength of affected limb due to hemiplegia,the use of dual mobility total hip arthroplasty can achieve good postoperative function and anti-dislocation effect.

Objective:To evaluate the application effect of management mode based on constraint theory for medical equipment in equipment management of vascular surgery. Methods:Based on five-step method of constraint theory,an operation evaluation system was formulated. An information management mode of medical equipment was constructed to manage quality of medical equipment in department of vascular surgery. A total of 60 sets used medical equipment in the Department of Vascular Surgery at The Second Affiliated Hospital of Xi'an Jiaotong University from 2021 to 2022 were selected. The conventional management mode was adopted to manage these equipment between January to December 2021,while equipment was managed by using medical equipment management mode based on constraint theory (constraint theory management) of the department of vascular surgery from January to December 2022. The quality scores of operation and maintenance of equipment,average incidence rates of risk,configuration effectiveness,and timeliness of equipment management were compared between the two management modes. Results:After constraint theory management was implemented,the average scores of operation and maintenance of equipment,which included success starting-up,operation,routine maintenance and fault repair,were respectively (90.69±8.65),(89.65±4.65),(88.65±5.63),and (90.58±6.01),all of which were higher than those of conventional management mode. The differences of them between two modes were statistically significant (t=13.482,17.867,14.552,14.449,P<0.05). The average incidence rates of the risks of testing equipment,treatment,monitoring equipment and auxiliary equipment of adopting constraint theory mode management were (0.89±0.22)％,(0.84±0.23)％,(0.74±0.32)％ and (0.75±0.32％),all which were lower than those of the conventional management mode,with statistically significant differences (t=9.162,17.745,19.469,15.019,P<0.05). The average utilization rate of equipment and the average amplification of cost benefit of equipment were respectively (88.69±5.54)％ and (50.36±2.69)％ after constraint theory mode was adopted,which were significantly higher than those of conventional management mode,and the average floating rate of using equipment of constraint theory mode was (1.23±0.97)％,which was lower than that of conventional management model,the differences of them between two modes were statistically significant (t=14.174,21.564,11.811,P<0.05). The average times of emergency management for risk events included the safety of power consumption of equipment,safety of diagnosis and treatment,biological safety and radiation safety were respectively (2.36±0.64)h,(3.26±0.78)h,(4.23±1.24)h and (2.26±1.23)h after the constraint theory mode was adopted,all of which were significantly less than those of conventional management mode,and the differences of them between two modes were statistically significant (t=16.704,13.421,9.029,13.971,P<0.05). Conclusion:The application of the management mode based on the constraint theory of medical equipment in department of vascular surgery can improve the quality of operation and maintenance of equipment for safety,and shorten the emergency response time of equipment,and reduce the incidence of equipment risk,and strengthen the effect of configuration for equipment.

Objective:To investigate the related factors of cognitive impairment in middle-aged and old-aged patients with type 2 diabetes mellitus(T2DM).Methods:A total of 970 patients with T2DM(585 middle-aged group and 385 old-aged group)were selected from residents of a large community in Beijing from September to December 2018.The Mini-Mental State Examination(MMSE)was used to assess the cognitive func-tion.Multivariate logistic regression was used to analyze the related factors.Results:The detection rates of cognitive impairment were 12.0％and 13.5％in middle-aged and old-aged patients with T2DM,respectively.Among mid-dle-aged patients with T2DM,work(OR=0.22,95％CI:0.03-0.77)and education at the junior college or un-dergraduate level and above(OR=0.18,95％CI:0.04-0.55)were protective factors for cognitive impair-ment.Myocardial infarction(OR=4.13,95％CI:1.26-13.63)was a risk factor for cognitive impairment.Among old-aged patients with T2DM,drinking tea 1-2 times a week(OR=0.11,95％CI:0.01-0.58)and education at the junior college or undergraduate level and above(OR=0.19,95％CI:0.05-0.54)were protective factors for cognitive impairment.Stroke(OR=3.64,95％CI:1.55-8.39)and good sleep self-assessment(OR=2.75,95％CI:1.13-7.35)were risk factors for cognitive impairment.Conclusion:Cognitive impairment in middle-aged pa-tients with T2DM is related to work,education level and myocardial infarction,and cognitive impairment in old-aged patients with T2DM is related to lifestyle,education level and stroke.