BACKGROUND:Nanocell vesicles possess functions such as re-epithelialization,antioxidation,anti-inflammation,and regulation of extracellular matrix remodeling.Meanwhile,apoptotic bodies have the immunomodulatory effects.Therefore,the combination of the two to form nanofusion vesicles can synergistically promote the healing of diabetic skin wounds.OBJECTIVE:To elucidate the impact of nanofusion vesicles on skin wound healing in a diabetic murine model.METHODS:(1)Material preparation and characterization:The primary bone marrow mesenchymal stem cells of C57BL/6J neonatal mice and the neutrophil apoptotic bodies of C57BL/6J mice were isolated and extracted.The nanofusion vesicles were prepared by micro-extrusion mechanism.(2)In vitro experiment:MTT assay was used to detect the proliferative effect of different concentrations of nanofusion vesicles on NIH-3T3 cells and human umbilical vein endothelial cells.Reactive oxygen species fluorescence probe was used to detect the antioxidant effect of nano-fusion vesicles on NIH-3T3 cells treated with hydrogen peroxide(H2O2).The inhibitory effect of nanofusion vesicles on RAW 264.7 macrophage inflammation induced by lipopolyside was detected by real-time quantitative RT-qPCR.(3)In vivo experiment:36 male C57BL/6J mice were employed to develop a murine model of diabetes mellitus.Following the successful induction of diabetes,two circular full-thickness wounds,each with a diameter of 6 mm,were created on either side of the diabetic mice's spine using a skin punch.The mice were divided into three groups by random number table method.The control group was injected with 0.1 mL of phosphate buffer solution.The nanovesicle group was injected with 0.1 mL nanovesicles(25 μg/mL).The nanofusion vesicle group was injected with 0.1 mL nanofusion(25 μg/mL)vesicles.After treatment for three consecutive days,the wound healing and histomorphological changes were observed.RESULTS AND CONCLUSION:(1)In vitro experiment:nanofusion vesicles,when administered at concentrations ranging from 0 to 100 μg/mL,exhibited no toxic effects and promoted the proliferation of NIH-3T3 and HUVEC cell lines.Notably,a concentration of 25 μg/mL nanofusion vesicle significantly enhanced the proliferation of NIH-3T3 cells.Furthermore,the survival rate of human umbilical vein endothelial cells was observed to increase in correlation with escalating concentrations of nanofusion vesicles.Nanofusion vesicles had a good antioxidant effect.In comparison to the H2O2 group,the fluorescence signal indicative of reactive oxygen species was progressively diminished in both the nanovesicle group and the nanofusion vesicle group.Furthermore,nanofusion vesicles possessed anti-inflammatory capabilities,effectively mitigating the inflammatory response in macrophages triggered by lipopolysaccharide stimulation.(2)In vivo experiment:Hematoxylin-eosin and Masson's trichrome staining revealed that in comparison to the control group,both the nanovesicle group and the nanofusion vesicle group exhibited a significant increase in granulation tissue formation and collagen fiber deposition within the wounds by day 6.Notably,the nanofusion vesicle group displayed the most pronounced effects.On day 12,the wound of nanofusion vesicle group was significantly reduced,and the healing rate was significantly faster than that of other groups(P＜0.01),and the effect of promoting wound healing was the most significant.Our findings demonstrated that nanofusion vesicles exhibited superior pro-cell proliferative,antioxidant,and anti-inflammatory properties,thereby exerting a beneficial effect on the promotion of skin wound healing in diabetic mouse models.

: To analyze the prevalence of anemia and iron deficiency among primary and secondary school students in Rural Nutrition Improvement Program areas of Guizhou Province in 2023, and to explore the related factors, so as to provide evidence for Rural Nutrition Improvement Program optimization. Methods: In September 2023, a stratified random cluster sampling strategy was used to select 40 rural compulsory education schools with rural nutrition improvement program in five counties of Guizhou Province. School level questionnaire was employed to collect information of basic characteristics and school meal implementation. A total of 7 826 primary and secondary school students aged 6-16 underwent anthropometry and hemoglobin (Hb) determination; serum ferritin (SF) was additionally measured in a random subsample of 1 795 pupils. Students in Grade 3 and above also completed a questionnaire covering demographic characteristics, dietary behaviours and nutrition knowledge. Group comparisons were conducted by Chi square test or Fisher s exact test, and multivariable Logistic regression models were constructed to identify factors associated with anemia and iron deficiency. Results: The overall Hb level was (133.21±12.95)g/L, with an anemia prevalence of 7.17%. The overall SF level was (69.58±59.01)μg/L, with an iron deficiency prevalence of 2.73%. Multivariable analysis showed that stunting ( OR =1.88), school menus without nutrient calculation ( OR =1.61) and absence of menu planning software in the current semester ( OR =2.34) independently increased anemia risk, whereas obesity reduced it ( OR =0.54) (all P <0.05). Girls ( OR =4.16) and Grades 7-9 ( OR =5.93) increased iron deficiency risk (both P <0.05). Compared with rarely eating fresh vegetables, students with consuming <3 kinds per day ( OR =0.08) or exactly 3 kinds per day ( OR =0.06) had lower iron deficiency risks (both P <0.05). Conclusions Anemia and iron deficiency are prevalent among primary and secondary school students in Guizhou. Targeted intervention measures should be implemented for key populations to enhance the effectiveness of nutrition improvement program.

BackgroundThe violent aggressive behaviors of patients with schizophrenia usually have the characteristics of suddenness， unpredictability， high severity， and great difficulty in prevention. Early identification and accurate assessment of their risk of violent aggression have significant clinical significance. ObjectiveTo construct a predictive model for the violence risk in hospitalized patients with schizophrenia， to identify the key factors influencing the occurrence of violent behavior in these patients， so as to provide references for clinical precise quantitative assessment and early intervention. MethodsA total of 200 patients with schizophrenia who were hospitalized at Taiyuan Psychiatric Hospital from March 2022 to September 2024 and met the diagnostic criteria of the International Classification of Diseases， eleventh edition （ICD-11） were collected to form the modeling cohort. They were randomly divided into a training set （n=140） and a test set （n=60） at a ratio of 7∶3. Based on the least absolute shrinkage and selection operator （LASSO） regression algorithm， the feature variables were screened and dimension-reduced. The support vector machine （SVM） from machine learning was selected for model training and prediction. The discrimination efficacy of the model was evaluated by the area under the receiver operating characteristic （ROC） curve （AUC）， accuracy， precision， sensitivity， specificity， F1 value， and Brier value. ResultsLASSO regression screening identified 16 feature variables. Pearson correlation analysis revealed a positive correlation between prior violent behavior frequency and clinical psychiatric symptom scores （r=0.580， P<0.01）， a positive correlation between hospitalization compliance and current disease status （r=0.550， P=0.003）， and a positive correlation between educational level and family per capita monthly income （r=0.367， P<0.01）. The SVM model achieved an AUC of 0.853， accuracy of 0.800， precision of 0.810， sensitivity of 0.895， specificity of 0.636， F1 value of 0.850， and Brier value of 0.168. ConclusionThe SVM model has a relatively high level of applicability and overall predictive performance in the assessment of violent risk in schizophrenia patients， which is helpful for the early identification of violent risks in such patients. ［Funded by Specialized Research Project for Enhancing the Competence of Health Professionals in Taiyuan City （number， Y2023006）］

BACKGROUND:Nanocell vesicles possess functions such as re-epithelialization,antioxidation,anti-inflammation,and regulation of extracellular matrix remodeling.Meanwhile,apoptotic bodies have the immunomodulatory effects.Therefore,the combination of the two to form nanofusion vesicles can synergistically promote the healing of diabetic skin wounds.OBJECTIVE:To elucidate the impact of nanofusion vesicles on skin wound healing in a diabetic murine model.METHODS:(1)Material preparation and characterization:The primary bone marrow mesenchymal stem cells of C57BL/6J neonatal mice and the neutrophil apoptotic bodies of C57BL/6J mice were isolated and extracted.The nanofusion vesicles were prepared by micro-extrusion mechanism.(2)In vitro experiment:MTT assay was used to detect the proliferative effect of different concentrations of nanofusion vesicles on NIH-3T3 cells and human umbilical vein endothelial cells.Reactive oxygen species fluorescence probe was used to detect the antioxidant effect of nano-fusion vesicles on NIH-3T3 cells treated with hydrogen peroxide(H2O2).The inhibitory effect of nanofusion vesicles on RAW 264.7 macrophage inflammation induced by lipopolyside was detected by real-time quantitative RT-qPCR.(3)In vivo experiment:36 male C57BL/6J mice were employed to develop a murine model of diabetes mellitus.Following the successful induction of diabetes,two circular full-thickness wounds,each with a diameter of 6 mm,were created on either side of the diabetic mice's spine using a skin punch.The mice were divided into three groups by random number table method.The control group was injected with 0.1 mL of phosphate buffer solution.The nanovesicle group was injected with 0.1 mL nanovesicles(25 μg/mL).The nanofusion vesicle group was injected with 0.1 mL nanofusion(25 μg/mL)vesicles.After treatment for three consecutive days,the wound healing and histomorphological changes were observed.RESULTS AND CONCLUSION:(1)In vitro experiment:nanofusion vesicles,when administered at concentrations ranging from 0 to 100 μg/mL,exhibited no toxic effects and promoted the proliferation of NIH-3T3 and HUVEC cell lines.Notably,a concentration of 25 μg/mL nanofusion vesicle significantly enhanced the proliferation of NIH-3T3 cells.Furthermore,the survival rate of human umbilical vein endothelial cells was observed to increase in correlation with escalating concentrations of nanofusion vesicles.Nanofusion vesicles had a good antioxidant effect.In comparison to the H2O2 group,the fluorescence signal indicative of reactive oxygen species was progressively diminished in both the nanovesicle group and the nanofusion vesicle group.Furthermore,nanofusion vesicles possessed anti-inflammatory capabilities,effectively mitigating the inflammatory response in macrophages triggered by lipopolysaccharide stimulation.(2)In vivo experiment:Hematoxylin-eosin and Masson's trichrome staining revealed that in comparison to the control group,both the nanovesicle group and the nanofusion vesicle group exhibited a significant increase in granulation tissue formation and collagen fiber deposition within the wounds by day 6.Notably,the nanofusion vesicle group displayed the most pronounced effects.On day 12,the wound of nanofusion vesicle group was significantly reduced,and the healing rate was significantly faster than that of other groups(P＜0.01),and the effect of promoting wound healing was the most significant.Our findings demonstrated that nanofusion vesicles exhibited superior pro-cell proliferative,antioxidant,and anti-inflammatory properties,thereby exerting a beneficial effect on the promotion of skin wound healing in diabetic mouse models.

Background/Aims: Liver transplantation (LT) following total hepatectomy is a life-saving treatment for hepatocellular carcinoma (HCC). The HCC recurrence after LT hinders the effectiveness of the procedure. The objective of this study is to develop a pre-operative risk stratification model based on a liquid biopsy. Methods: We conducted a comprehensive multi-omics study of 260 HCC patients from three centers, including clinical data, low-coverage whole-genome sequencing of cell-free DNA (cfDNA) from plasma, as well as whole-exome, single-nucleus RNA, and spatial transcriptomics from matched tumor and non-tumor tissues. Results: We identified cfDNA-derived copy number alteration (CNA) signatures associated with post-transplant recurrence. By integrating cfDNA-derived CNA profiles with single-cell transcriptomic data, we traced recurrence-associated cfDNA to a distinct subpopulation of malignant cells within the primary tumor. These cells were embedded in a pro-metastatic microenvironment of specialized endothelial subtypes and cancer-associated fibroblasts. Notably, most recurrence-associated lesions were detectable in cfDNA prior to liver transplantation (LT). Building on these insights, we developed the ZJU Criteria based on CNA fragments and tumor markers, a pre-LT risk prediction tool that integrates conventional clinical factors with cfDNA-derived CNA signatures, and validated it using internal and independent external cohorts. Conclusion Our findings suggest that post-transplant recurrence commonly originates from advanced subclones that emerge late during tumor evolution. The ZJU Criteria provides an accurate, non-invasive strategy that significantly improves pre-LT risk stratification and clinical decision-making for patients with HCC.

With the continuous deepening of the concept of precision diagnosis and treatment for lung cancer, how to achieve higher efficiency and accuracy in the screening, diagnosis, and treatment pathways in clinical practice has become an important issue that urgently needs to be overcome. The current clinical difficulty lies in the fact that despite continuous advancements in imaging and molecular diagnostic technologies, there are still limitations in manual efficiency and subjective experience when it comes to massive data analysis and multi-scale feature extraction. Artificial intelligence (AI), especially algorithm systems based on deep learning, is an innovative technology capable of deeply empowering medical big data. This method utilizes algorithms such as convolutional neural networks, combined with radiomics, pathomics, and multi-modal data fusion analysis, demonstrating immense potential in early precise detection and benign-malignant differentiation of pulmonary nodules, digital pathological subtype recognition and non-invasive prediction of driver genes, precise 3D surgical planning and automatic delineation of radiotherapy target volumes, as well as dynamic risk warning during follow-up. This innovative technology provides a brand-new solution for realizing intelligent and individualized lung cancer diagnosis and treatment models. This consensus, based on the latest evidence from evidence-based medicine and combined with the development trends in the AI field and real-world clinical needs, was ultimately formed by gathering the consensus opinions of multidisciplinary experts in radiology, pathology, thoracic surgery, and other fields. The main content covers the application specifications of AI in the three core scenarios of lung cancer screening, diagnosis, and treatment, the technical standards for data collection and algorithm validation, as well as the ethical and regulatory challenges faced at the current stage. It aims to clarify the applicable boundaries of AI as a clinical auxiliary decision support tool, providing scientific guidance and standardized exploration directions for peers currently engaged in or planning to carry out AI-assisted clinical diagnosis, treatment, and translation of lung cancer.

The mental health management of laboratory animals is a critical factor in ensuring the reliability of scientific research data. However, due to the subtle nature of mental state alterations and the limitations of current assessment methods, the mental health of laboratory animals is often overlooked by researchers. Therefore, there is an urgent need to explore a new, objective, simple, and practical method for evaluating mental health. Stress, as a primary factor inducing alterations in the mental state of animals, can influence experimental results across multiple research fields through the neuroendocrine-immune network. This paper first elucidates the necessity of mental health management in laboratory animals from three perspectives: factors contributing to stress, neural mechanisms of stress, and research areas affected by stress. It highlights that excluding animals with abnormal mental states before experiments can enhance the efficiency and reproducibility of biomedical studies. Second, this paper briefly summarizes existing methods for assessing the health of laboratory animals, pointing out that approaches such as behavioral tests and metabolomics have many limitations in evaluating stress responses. Existing methods struggle to meet the demand for simple, objective, and non-invasive assessment methods in animal management. Therefore, this paper focuses on hair, a biological sample with the advantages of cumulative information and non-invasive collection, and systematically describes the theoretical basis and technological advances in using hair characteristics as indicators of stress responses from three perspectives: hair traits, the levels of substances in hair, and artificial intelligence (AI). It proposes and supports an innovative technical pathway that combines hair traits with AI-based image analysis, with the aim of offering an improved solution for non-invasive and objective stress assessment, while providing theoretical support for improving the health management system of laboratory animals.

Objective On the basis of the theory of the tumor metastatic state, this work aims to explore the metastasis trajectories and peripheral immune response patterns in patients with non-small cell lung cancer (NSCLC) receiving vital qi-strengthening and toxin-eliminating therapy (Fuzheng Juandu) and reveal the value of peripheral immunity in assessing vital qi deficiency during metastasis. Methods A retrospective study design was adopted. Patients with NSCLC admitted from January 1, 2018, to October 31, 2025 were enrolled. Data on metastasis status and peripheral immune indices were collected at the follow-up time points of one, two, three, and five years. Group-based trajectory modeling was used to fit metastasis trajectories, and the independent predictors of trajectory grouping were analyzed through multifactor and multiclassification logistic regression. Results A total of 184 patients with NSCLC were included, and three different groups of metastasis trajectories were identified, namely, the low-risk stable (46.74%, n=86), low-risk rising (13.59%, n=25), and high-risk stable (39.67%, n=73) groups. Univariate analysis revealed substantial differences in peripheral immune indices among the three trajectory groups. Multivariate analysis showed that TNM stage, absolute neutrophil count, lymphocyte count, absolute monocyte count, platelet volume, SAA:CRP ratio, and NLR were independent predictors of the low-risk rising group, whereas TNM stage, absolute monocyte count, basophil count, SII, and NLR were independent predictors of the high-risk stable group. Conclusion Under Fuzheng Juandu therapy, patients with NSCLC exhibit three distinct metastasis trajectories, each corresponding to a specific peripheral immune response pattern. Elucidating these peripheral immune response patterns may facilitate the objective quantification of the degree of vital qi deficiency, prediction of future metastasis risk, and providing an important reference for the individualized clinical implementation of Fuzheng Juandu therapy.

OBJECTIVE To evaluate the cost-effectiveness of brivaracetam （BRV） versus perampanel （PER） as add-on therapy for drug-resistant focal epilepsy in adults from the perspective of the Chinese healthcare system.METHODS A Markov model was established to simulate the progression of drug-resistant focal epilepsy in adults， with a simulation cycle of 5 months， a time horizon of 44 years， and a discount rate of 4.5%. Clinical data required for the model were derived from the phase Ⅲ clinical trial of BRV and a post hoc analysis of PER； cost data and utility data were obtained from Yaozh and related literature. The willingness-to-pay （WTP） threshold was set at twice China’s 2025 per capita gross domestic product （GDP） [199 330 yuan per quality-adjusted life year （QALY）]， and a cost-effectiveness analysis was adopted to compare the cost-effectiveness of the regimens. One-way sensitivity analysis and probabilistic sensitivity analysis were performed to confirm the stability of the base-case analysis conclusions.RESULTS The incremental cost-effectiveness ratio （ICER） of BRV 50 mg/d as an add-on therapy versus PER 8 mg/d was 44 823.08 yuan/QALY， which was below the WTP threshold； the ICER of BRV 200 mg/d versus PER 12 mg/d was 238 783.00 yuan/QALY， which was above the WTP threshold. In the one-way sensitivity analysis， the direct medical cost of seizures ≥53 times/year and the health utility value of a seizure-free state per year had a relatively large impact on the two ICER results mentioned above， respectively. Probabilistic sensitivity analysis indicated that the above results were robust.CONCLUSIONS For the selection of add-on therapy for drug-resistant focal epilepsy in adults in China， when twice China’s per capita GDP is used as the WTP threshold， BRV 50 mg/d has a cost-effectiveness advantage over PER 8 mg/d， whereas BRV 200 mg/d not have a cost-effectiveness advantage over PER 12 mg/d.

OBJECTIVE To mine the risk signals associated with erectile dysfunction （ED） related to antihypertensive drugs based on real-world data， and to provide a reference for the safe clinical use and risk monitoring of these drugs.METHODS Reports of ED associated with 15 target antihypertensive drugs were extracted from the US FDA Adverse Event Reporting System （FAERS） database， covering the period from the first quarter of 2004 to the first quarter of 2026. Three proportional disproportionality measures （reporting odds ratio， proportional reporting ratio， and empirical Bayesian geometric mean） were used to mine the risk signals for ED associated with various antihypertensive drugs， and stratified analyses were performed based on patient age and body weight.RESULTS A total of 997 ED reports associated with 15 antihypertensive drugs were included. The majority were male patients （931 reports）， with age concentrated in the 18 to ＜65 years group （511 reports）， body weight in the 50 to ＜100 kg group （366 reports）， and reporters predominantly consumers/patients （497 reports）. The top three drugs by number of reports were amlodipine （413 reports）， metoprolol （133 reports）， and valsartan （82 reports）； the overall demographic distribution characteristics of reports associated with each drug were similar. Positive signals were detected for 8 drugs， including amlodipine and metoprolol. ED associated with atenolol， candesartan， metoprolol， hydrochlorothiazide， and losartan mostly occurred within 30 days after medication； ED associated with valsartan and perindopril mostly occurred over 360 days after medication； and the onset time of amlodipine-associated ED was evenly distributed across all time periods. There were a total of 835 serious reports， with calcium channel blockers （CCBs） accounting for the highest proportion （44.0%） and angiotensin-converting enzyme inhibitors for the lowest （3.7%）. The intensity of risk signals for amlodipine-associated ED increased with advancing age and higher body weight， while the signals for metoprolol were most pronounced in individuals aged 45 to ＜60 years and weighing≥100 kg； positive signals for valsartan were observed only in individuals aged≥60 years and those weighing 50 to ＜75 kg or ≥100 kg.CONCLUSIONS Reports of ED associated with antihypertensive drugs exhibit significant heterogeneity across drug types and differences in the distribution of onset times； CCBs have the highest proportion of serious reports； and the relationship between ED risk signals associated with amlodipine， metoprolol， and valsartan and age and body weight also shows marked heterogeneity.