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.

Depressive disorder is a kind of mental disorder characterized by persistent and significant depressed mood, with complex etiology and high recurrence rate. At present, more precise and effective diagnostic and therapeutic approaches are still required. Increasing evidence suggests that hypoxia inducible factor-1 (HIF-1) and related pathways are involved in regulating the development and recovery of depression. HIF-1 enhances neuroplasticity, mitigates neuroinflammatory responses, alleviates oxidative stress, and modulates brain energy metabolism by influencing specific molecules associated with depression. This paper reviews pertinent domestic and international studies, examine the potential mechanisms of HIF-1 in the pathogenesis and progression of depression, and explore antidepressant treatment strategies targeting the HIF-1 signaling pathway. This article provides novel insights into elucidating the pathogenesis of depression and developing innovative therapeutic approaches.

Objective:To study the mechanism of arsenic trioxide(ATO)combined with metformin(MET)in promoting apoptosis of leukemia cells.Methods:CCK-8 method was used to detect the viability of leukemia cell line KG1a,K562,and THP1 cells treated by ATO monotherapy,MET monotherapy,and ATO combined with MET.Flow cytometry was used to detect cell cycle and apoptosis.RT-qPCR was used to detect the mRNA expression of PI3K/Akt and LKB1/AMPK pathway-related genes.Western blot was used to detect the expression of PI3K/Akt and LKB1/AMPK pathway-related proteins and autophagy-related protein LC3B and P62.Results:Compared with the ATO monotherapy group,ATO combined with MET significantly inhibited the growth of KG1a,K562 and THP1 cells,and the difference in KG1a cells was more statistically significant.The combination of the two drugs induced KG1a cell cycle arrest,promoted apoptosis,increased the expression of autophagy-related protein LC3B and P62,up-regulated the mRNA expression levels of PI3K/Akt pathway and LKB1/AMPK pathway-related genes,as well as the expression of LKB1/AMPK pathway-related proteins,and down-regulated the expression of PI3K/Akt pathway-related proteins.Conclusion:ATO combined with MET promotes apoptosis by up-regulating LKB1/AMPK and down-regulating PI3K/Akt signaling pathway to regulate the autophagy of leukemia cells.

Objective To investigate the effects of TEK receptor tyrosine kinase(Tie2)L914F mutation on the biological behavior of vascular endothelial cells and the changes of related signaling pathways in patients with venous malformations.Methods Gene sequen-cing was used to detect Tie2-L914F mutations in venous malformations.HE staining and immunohistochemical staining were used to de-tect the expression of platelet derived growth factor subunit B gene(PDGFB)and α-smooth muscle actin(α-SMA)in venous malfor-mations caused by the mutation.Lentivirus overexpressing Tie2-wild type(Tie2-WT),Tie2-L914F and Tie2-GFP(green fluorescent protein,GFP)infected human umbilical vein endothelial cells(HUVECs).Real-time fluorescence quantitative PCR was used to detect the expression level of Tie2 in endothelial cells expressing exogenous Tie2 and Flag-tagged protein Tie2 protein was detected by western blotting to verify transfection efficiency.The proliferation,apoptosis,migration and tube-forming ability of the cells were determined by CCK-8,flow cytometry,Transwell migration assay and Matrigel matrix gel tube-forming assay.Western blotting was used to detect the expression levels of Protein Kinase B(PKB/AKT),FOXO1 and their phosphorylation,and the expression level of PDGFB was detec-ted by ELISA.Results The number of patients with venous malformations with L914F mutations was about 33.3％.HE and immuno-histochemical staining showed that the expressions of PDGFB and α-SMA were significantly down-regulated in venous malformation tis-sues with Tie2-L914F mutation,and were positively correlated with the decrease in cell coverage of the tube wall.Compared with Tie2-WT endothelial cells,the apoptosis number of Tie2-L914F endothelial cells was significantly reduced,while the proliferation and mi-gration ability was significantly increased,and the tube-forming ability was significantly decreased.Western blotting and ELISA showed that the phosphorylation levels of AKT and FOXO1 downstream of Tie2 signaling pathway in endothelial cells expressing Tie2-L914F were significantly increased,and the expression level of PDGFB was significantly decreased.Conclusion In venous malformations,Tie2-L914F mutation may downregulate the expression of PDGFB through AKT signaling pathway,which affects the biological behavior of vascular endothelial cells.

Clinical teaching managers are the designers, implementers, and supervisors of clinical medical education. Their competence level directly affects the quality of hospital teaching management and clinical medical education. The competence evaluation systems for medical education managers in countries such as the United States and the United Kingdom are well-established, which provides a reference for the competence evaluation of clinical teaching managers in China. This research systematically reviews the construction process and current situation of the competence evaluation systems for medical education managers in the world, and summarizes the basis, methods, and dimensions of competence evaluation. According to the actual situation of clinical teaching management, suggestions were put forward, including developing systematic scientific evaluation tools, carrying out competence-oriented training and assessment, focusing on student-centered education, and creating a career path of sustainable development.

Objective To develop and validate a transgenic mouse model enabling specific and inducible optogenetic activation of oligodendrocyte precursor cells(OPCs).Methods A conditional allele for the photosensitive opsin chicken opsin 5(cOpn5)(Rosa26-LSL-cOpn5)was generated using CRISPR/Cas9 technology.These mice were subsequently crossed with NG2-CreERT transgenic mice to produce NG2-CreERT;cOpn5 animals.In this model,tamoxifen administration induces Cre-mediated recombination,leading to specific expression of cOpn5 in NG2-positive OPCs.The specificity and efficiency of cOpn5 expression in OPCs were confirmed by immunofluorescent staining.Functional validation of light-induced OPC activation was performed by using calcium imaging in acute brain slices after stimulation with 470 nm blue light.Results Immunofluorescence analysis confirmed robust and specific expression of cOpn5 within NG2-positive OPCs in the brains of tamoxifen-treated NG2-CreERT;cOpn5 mice.Crucially,calcium imaging of acute brain slices from these mice demonstrated a significant increase in intracellular calcium levels in cOpn5-expressing OPCs upon stimulation with 470 nm blue light,indicating successful optogenetic activation.Conclusion We have successfully generated and validated a novel transgenic mouse model(NG2-CreERT;cOpn5)that permits specific and inducible optogenetic activation of OPCs.This model provides a novel tool for subsequent in vivo studies of the role and regulating mechanisms of OPCs in the central nervous system.

Objective:To investigate the application value of risk prediction model for acute kidney injury (AKI) after donation of cardiac death (DCD) liver transplantation based on machine learning algorithm.Methods:The retrospective cohort study was conducted. The clinicopathological data of 1 001 pairs of DCD liver transplant donors and recipients at five hospitals, including The First Affiliated Hospital of Zhejiang University School of Medicine et al, in the Chinese Liver Transplan-tation Registry from January 2015 to December 2023 were collected. Of the donors, there were 825 males and 176 females. Of the recipients, there were 806 males and 195 females, aged 52 (range, 18-75)years. There were 281 recipients included using oversampling technique, and all 1 282 recipients were divided to the training set of 897 recipients and the validation set of 385 recipients by a ratio of 7∶3 using computer-generated random numbers. Seven prediction models, including Random Forest (RF), Extreme Gradient Boosting (XGBoost), Support Vector Machine (SVM), Logistic Regression (LR), Decision Tree (DT), K-Nearest Neighbors (KNN), and Categorical Boosting (CatBoost), were constructed for AKI after liver transplantation based on machine learning algorithm. Observation indicators: (1) comparison of clinicopathological characteristics between recipients with and without AKI and donors; (2) follow-up and survival of recipients with and without AKI; (3) construction and validation of nomogram prediction model of AKI after liver transplantation; (4) construction and validation of machine learning prediction model of AKI after liver transplantation. Comparison of measurement data with normal distribution between groups was conducted using the independent sample t test. Comparison of measurement data with skewed distribution between groups was conducted using the Mann-Whitney U test, and comparison among groups was conducted using the Kruskal-Wallis H test. Comparison of count data between groups was conducted using the chi-square test or corrected chi-square test. Kaplan-Meier method was used to calculate survival rates and plot survival curves. Logistic regression model was performed for univariate and multivariate analyses. The receiver operating characteristic (ROC) curve was plotted to calculate area under curve (AUC) and 95% confidence interval ( CI). The performance of prediction model was evaluated using DeLong test, accuracy, sensitivity, specificity. The calibration curve was plotted to evaluate the performance of predicted probability and actual probability. The interpretability analysis of machine learning algorithm and SHapley Additive exPlanations was used to explain the model decision separately. Results:(1) Comparison of clinicopathological characteristics between recipients with and without AKI and donors. Of 1 001 recipients, there were 360 cases with AKI and 641 cases without AKI after liver transplantation. There were significant differences in body mass index (BMI), hepatic encepha-lopathy, hepatitis B surfact antigen (HBsAg), hepatorenal syndrome (HRS) and donor diabetes, donor blood urea nitrogen, donor alanine aminotransferase, donor aspartate aminotransferase, mass of graft, volume of blood loss during liver transplantation, warm ischema time of donor liver, and operation time between recipients with and without AKI ( Z=-4.337, χ2=9.751, 9.088, H=11.142, χ2=5.286, Z=-3.360, -2.539, -3.084, -1.730, -3.497, -1.996, -2.644, P<0.05). (2) Follow-up and survival of recipients with and without AKI. All the 1 001 recipients received follow-up. The recipients with AKI after liver transplantation were followed up for 18.6(range, 0-102.3)months, and recipients without AKI after liver transplantation were followed up for 31.9(range, 0.1-105.5)months. The 1-, 3-, and 5-year overall survival rates were 72.1%, 63.5%, and 59.3% of recipients with AKI, versus 86.7%, 76.7%, and 72.5% of recipients without AKI, respectively, showing a significant difference in overall survival between them ( χ2=26.028, P<0.05). (3) Construction and validation of nomogram predic-tion model of AKI after liver transplantation. Results of multivariate analysis showed that recipient BMI, recipient creatinine, recipient HBsAg, recipient HRS, donor blood urea nitrogen, donor crea-tinine, anhepatic phase and volume of blood loss during liver transplantation were independent risk factors for AKI of recipients after liver transplantation ( odds ratio=1.113, 0.998, 0.605, 1.580, 1.047, 0.998, 1.006, 1.157, 95% CI as 1.070-1.157, 0.996-1.000, 0.450-0.812, 1.021-2.070, 1.021-1.074, 0.996-0.999, 1.000-1.012, 1.045-1.281, P<0.05). The nomogram prediction model of AKI after liver transplantation was constructed based on the results of multivariate analysis. Results of ROC curve showed that the AUC of 0.666 (95% CI as 0.637-0.696). (4) Construction and validation of machine learning prediction model of AKI after liver transplantation. Based on the Lasso regression analysis, seven machine learning algorithm prediction models, including RF, XGBoost, SVM, LR, DT, KNN, and CatBoost, were constructed, with ROC curves of the validation set plotted. The AUC of above models were 0.863, 0.841, 0.721, 0.637, 0.620, 0.708, 0.731, accuracies were 0.764, 0.782, 0.701, 0.592, 0.605, 0.605, 0.681, sensitivities were 0.764, 0.789, 0.719, 0.588, 0.694, 0.694, 0.704, specificities were 0.763, 0.774, 0.683, 0.597, 0.511, 0.511, 0.656, respectively. Delong test showed that the RF model with the highest AUC of 0.863(95% CI as 0.828-0.899). Calibration curve analysis showed the predicted probability closest to the actual probability of RF model, indicating the model with a good validation value. Further sorting of SHAP of different clinical factors based on RF model showed that recipient BMI, donor blood urea nitrogen, volume of blood loss during liver transplantation, donor age had large effects on the output outcomes. Conclusion:The nomogram prediction model and seven machine learning algorithm prediction models for AKI after DCD liver transplantation are constructed, and the RF model based on machine learning has a better predictive performance.

Objective To investigate the effect of tissue-resident memory T cells(TRM)on imiquimod-induced psoriatic-like skin lesions in mice,and to elucidate the underlying mechanisms of TRM involvement in this process.Methods Forty female BALB/c mice were procured and randomly allocated into four groups:ten in the blank control group,and thirty for the establishment of a psoriasis mouse model.Following successful modeling,the thirty mice were further randomized into three groups:the model control group,the methotrexate-treated group,and the imiquimod-treated group,with ten mice in each group.Mice in the blank control group and model control group were uniformly treated with Vaseline for intervention.The methotrexate group and the imiquimod group were treated with 62.5mg of 5％imiquimod cream.The methotrexate group was administered by gavage at a dose of 1 mg/kg,and the gavage volume of each group was 10 mL/kg.The model control group,blank group and imiquimod group were gavaged with the same volume of normal saline.Treatment was conducted over six consecutive days.Subsequently,comparisons were made across groups regarding the psoriasis area and severity index(PASI),histopathological findings,inflammatory cytokine levels,and TRM cell levels.Results(1)The imiquimod group exhibited signifi-cantly lower scores for erythema(2.54±0.32),skin thickening(2.59±0.25),and scaling(2.52±0.29)compared to the methotrexate group,model control group,and blank control group(P<0.05).Additionally,the methotrexate group demonstrated reduced scores for erythema,skin thickening,and scaling compared to the model control group(P<0.05).(2)Hematoxylin-eosin(HE)staining revealed that the epidermis in the methotrexate group became thin-ner,with fewer parakeratotic cells and increased hair follicles.Conversely,the imiquimod group displayed abnor-mal cell morphology and relatively thicker white skin after modeling.(3)The imiquimod group showed significantly lower levels of TNF-α(51.63±4.39 pg/mL),IL-1β(35.53±4.15 pg/mL),IFN-γ(23.43±3.41 pg/mL),and IL-23(15.24±2.95 pg/mL)compared to the methotrexate and model control groups(P<0.05).Similarly,the methotrexate group exhibited reduced levels of TNF-α,IL-1β,IFN-γ,and IL-23 compared to the model control group(P<0.05).(4)The imiquimod group had significantly lower levels of CD8+CD103+cells(15.39±2.31)than the methotrexate and model control groups(P<0.05).Furthermore,the methotrexate group demonstrated lower levels of CD8+CD103+cells compared to the model control group(P<0.05).Conclusion Miquimod induces heavier skin lesions,faster response,and more epidermal thickening in psoriasis like mice.CD8+CD103+TRM cells and inflammatory factors may be involved in the recurrence of psoriasis.

Depressive disorder is a kind of mental disorder characterized by persistent and significant depressed mood, with complex etiology and high recurrence rate. At present, more precise and effective diagnostic and therapeutic approaches are still required. Increasing evidence suggests that hypoxia inducible factor-1 (HIF-1) and related pathways are involved in regulating the development and recovery of depression. HIF-1 enhances neuroplasticity, mitigates neuroinflammatory responses, alleviates oxidative stress, and modulates brain energy metabolism by influencing specific molecules associated with depression. This paper reviews pertinent domestic and international studies, examine the potential mechanisms of HIF-1 in the pathogenesis and progression of depression, and explore antidepressant treatment strategies targeting the HIF-1 signaling pathway. This article provides novel insights into elucidating the pathogenesis of depression and developing innovative therapeutic approaches.

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.