Objective To explore the feasibility and reference value of allogeneic lung transplantation and postoperative monitoring in miniature pigs for lung transplantation research. Methods Two miniature pigs (R1 and R2) underwent left lung allogeneic transplantation. Complement-dependent cytotoxicity tests and blood cross-matching were performed before surgery. The main operative times and partial pressure of arterial oxygen (PaO₂) after opening the pulmonary artery were recorded during surgery. Postoperatively, routine blood tests, biochemical blood indicators and inflammatory factors were detected, and pathological examinations of multiple organs were conducted. Results The complement-dependent cytotoxicity test showed that the survival rate of lymphocytes between donors and recipients was 42.5%-47.3%, and no agglutination reaction occurred in the cross-matching. The first warm ischemia times of D1 and D2 were 17 min and 10 min, respectively, and the cold ischemia times were 246 min and 216 min, respectively. Ultimately, R1 and R2 survived for 1.5 h and 104 h, respectively. Postoperatively, in R1, albumin (ALB) and globulin (GLB) decreased, and alanine aminotransferase increased; in R2, ALB, GLB and aspartate aminotransferase all increased. Urea nitrogen and serum creatinine increased in both recipients. Pathological results showed that in R1, the transplanted lung had partial consolidation with inflammatory cell infiltration, and multiple organs were congested and damaged. In R2, the transplanted lung had severe necrosis with fibrosis, and multiple organs had mild to moderate damage. The expression levels of interleukin-1β and interleukin-6 increased in the transplanted lungs. Conclusions The allogeneic lung transplantation model in miniature pigs may systematically evaluate immunological compatibility, intraoperative function and postoperative organ damage. The data obtained may provide technical references for subsequent lung transplantation research.

Objective: To investigate the prevalence of comorbidity of myopia, and overweight and obesity among primary and middle school students in Yanqing District, Beijing Municipality, so as to provide the evidence for \prevention and control of comorbidity. Methods: In September from 2020 to 2024, a stratified cluster sampling method was adopted annually to select primary, junior high school, senior high school, and vocational high school students in Yanqing District as survey subjects. Myopia was screened based on Screening Protocol for Myopia in Children and Adolescents. Height an weight were measured, and overweight and obesity were determined using the Screening for overweight and Obesity in School-Age Children and Adolescents. Results: A total of 9 883 individuals were surveyed, including 5 219 primary school students (52.81%), 2 486 junior high school students (25.15%), and 2 178 senior high school / vocational high school students (22.04%). There were 5 154 boys (52.15%) and 4 729 girls (47.85%). From 2020 to 2024, the numbers of primary and middle school students in Yanqing District with myopia, overweight, and obesity were 4 426, 1 897, and 3 164, respectively, with detection rates of 44.78%, 19.19%, and 32.01%. The detection rates of myopia, overweight, and obesity showed an increasing trend with the elevation of school stage (all P<0.05). The detection rate of myopia was higher in girls than in boys, while the detection rate of obesity was lower in girls than in boys (all P<0.05). There were 2 588 individuals with both myopia and overweight/obesity, representing a detection rate of 26.19%, which showed an increasing trend (P<0.05), rising from 25.04% in 2020 to 34.41% in 2024. The detection rates of comorbidity of myopia, and overweight and obesity among primary school, junior high school, and senior high school / vocational high school students were 13.22%, 36.93%, and 45.00%, respectively, showing an increasing trend with the elevation of school stage (P<0.05). The difference between genders was not statistically significant (P>0.05). Conclusions The detection rates of comorbidity of myopia, and overweight and obesity among primary and middle school students in Yanqing District is relatively high and shows an upward trend, with students in higher school stage being the key target group for prevention and control. It is recommended to strengthen health education on the co-prevention of multiple health issues and implement differentiated interventions based on school stages.

OBJECTIVE To develope a predictive model for medication deviation risks during the hospital-to-home transition period in coronary heart disease （CHD） patients with initial treatment， aiming to assist medical staff in rapidly identifying high-risk groups for medication deviation. METHODS A total of 462 CHD patients with initial treatment from the Affiliated Hospital of North China University of Science and Technology （hereinafter referred to as “our hospital”） between January and July 2024 were enrolled. The patients were randomly divided into a modeling group and an internal validation group. The modeling group was further categorized into a medication deviation group and a non-medication deviation group based on whether medication deviations occurred. Similarly， 57 CHD patients with initial treatment from the cardiology department of our hospital between June and September 2025 were collected as an external validation group. Univariate analysis was used to screen predictive factors， followed by multivariate Logistic regression to construct the predictive model. Internal validation methods were employed to evaluate model performance， while external validation methods were used to test the model’s generalizability. RESULTS The 462 patients were divided into a modeling group （319 cases） and an internal validation group （143 cases）. In the modeling group， the medication deviation group （192 cases， 60.19%） and the non-medication deviation group （127 cases， 39.81%） were identified. Multivariate Logistic regression analysis revealed that age， medication type， medication adherence， and self-efficacy in rational medication use were predictive factors for medication deviations in CHD patients with initial treatment （ P ＜0.05）. The predictive model equation was logit P ＝ln[ P /（1－ P ） ] ＝1.321+1.732×age+4.091×medication type －4.360×medication adherence －3.081×self-efficacy in rational medication use. The model demonstrated good discrimination， with a Hosmer-Lemeshow goodness-of-fit test P -value of 0.439， an area under the receiver operating characteristic curve （AUC） of 0.870， sensitivity of 0.970， and specificity of 0.607. A risk nomogram with a total score of 350 points and a cutoff value of 110 points was plotted. The internal validation group showed an AUC o f 0.787 and a prediction accuracy of 77.6%， while the external validation group exhibited an AUC of 0.802 and a prediction accuracy of 73.7%. CONCLUSIONS This study successfully developed a predictive model for medication deviation risks during the hospital-to-home transition period in CHD patients with initial treatment. The model demonstrates excellent discrimination and predictive accuracy， effectively identifying high-risk populations for medication deviations. Age （＞70 years）， number of drug types≥5， poor medication adherence， and poor self-efficacy in rational medication use are independent risk factors for medication deviations.

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）］

Objective To develop a predictive model for postoperative pulmonary complications (PPC) following video-assisted thoracic surgery (VATS) in lung cancer patients by integrating cardiopulmonary exercise testing (CPET) parameters and machine learning techniques. Methods A retrospective analysis was conducted on patients with early-stage non-small cell lung cancer who underwent CPET and VATS at Guangdong Provincial People’s Hospital between October 2021 and July 2023. Patients were divided into a PPC group and a non-PPC group. The least absolute shrinkage and selection operator (LASSO) regression was used to select important features associated with PPC. Six machine learning algorithms were utilized to construct prediction models, including logistic regression, support vector machine, k-nearest neighbors, random forest, gradient boosting machine, and extreme gradient boosting. The optimal model was interpreted using SHapley Additive exPlanations (SHAP). Results A total of 325 patients were included, with an average age of 60.36 years, and 55.1% were male. Significant differences were observed between the PPC and non-PPC groups in age, diabetes, coronary heart disease, surgical approach, forced expiratory volume in 1 second (FEV1), forced vital capacity (FVC), FVC% predicted, peak oxygen uptake (peak VO2), anaerobic threshold (AT), and ventilatory equivalent for carbon dioxide slope (VE/VCO2 slope) (P<0.05). In the predictive model constructed by selecting 7 key features using LASSO regression, the random forest model demonstrated the best overall performance across various metrics, with an area under the receiver operating curve of 0.930, an F1 score of 0.836, and a Brier score of 0.133 in the training set. It also exhibited good predictive ability and calibration in the test set. SHAP analysis ranked feature importance as follows: peak VO2, VE/VCO2 slope, age, FEV1, smoking history, diabetes, and surgical approach. Conclusion Integrating CPET parameters, the random forest model can effectively identify high-risk patients for PPC and has the potential for clinical application.

Objective To analyze the newly reported HIV-1 infection in several prefectures of Hubei Province，and analyze its influencing factors. Methods The limiting antigen avidity enzyme immunoassay(LAg-avidity EIA,LAg) was conducted on HIV-1 positive samples confirmed by Western blot of Hubei in 2017-2022. The demographic characteristics of the newly infected samples were analyzed by χ2 test.Logistic regression model was used to analyze influencing factors of new infection rate and predict the factors associated with the HIV-1 recent infection. Results There were 403 new cases of HIV-1 from 2017 to 2022 in several prefectures of Hubei Province, of which 77 were newly infected sorted by LAg,with a new infection rate of 19.11%. The newly confirmed HIV-1 persons of whom aged ≤24 years (40.00% new infection ratio), unmarried (29.41%), college or above (31.37%), and from Voluntary counseling and testing testing(VCT) clinics (40.00%) had a higher proportion of new infections, and the difference was statistically significant. Multivariate Logistic regression analysis showed that age ≤24 years old (aOR=4.346,95%CI: 1.342-14.075) and screening from the VCT clinic (aOR=6.761,95%CI: 1.460-31.319) were more likely to be newly infected. Conclusion The proportion of new HIV infection in several prefectures of Hubei province is relatively low in recent years.Further effective publicity and intervention measures for young students and the construction of VCT clinic should be continuously promoted to achieve early diagnosis and treatment.

Background: Delirium in the post-anesthesia care unit (PACU) may be associated with worse outcomes in children with moyamoya disease (MMD). This retrospective study aimed to describe the prevalence of PACU delirium in children with MMD and investigate its risk factors. Methods: Patients with MMD aged < 15 years who underwent indirect revascularization between January 2014 and October 2023 were included in this study. Delirium was assessed using the Pediatric Anesthesia Emergence Delirium Scale. Potential risk factors for PACU delirium were evaluated using multivariate logistic regression. Results: PACU delirium occurred in 245 (33%) of the 750 hemispheric procedures performed in 522 patients. Delirium was associated with a higher incidence in patients undergoing the first revascularization (37%) than in those undergoing the second (25%; P = 0.002). Cerebral infarction as the initial presentation (odds ratio [OR]: 4.64, first revascularization), high pediatric moyamoya magnetic resonance imaging (MRI) score (OR: 2.75, first revascularization; OR: 3.50, second revascularization), and high intraoperative mean arterial pressure variability (mmHg/min) (OR: 9.17, first revascularization; OR: 8.82, second revascularization) were associated with PACU delirium. Conversely, total intravenous anesthesia (TIVA) was associated with a lower incidence of PACU delirium (OR: 0.46, first revascularization; OR: 0.25, second revascularization). Conclusions A significant proportion of patients with MMD developed delirium in the PACU. High intraoperative blood pressure variability and preoperative MRI lesions are independent risk factors for PACU delirium in children with MMD. TIVA may exert a protective effect against PACU delirium. Further studies are required to clarify the causality of these associations.

Background: Delirium in the post-anesthesia care unit (PACU) may be associated with worse outcomes in children with moyamoya disease (MMD). This retrospective study aimed to describe the prevalence of PACU delirium in children with MMD and investigate its risk factors. Methods: Patients with MMD aged < 15 years who underwent indirect revascularization between January 2014 and October 2023 were included in this study. Delirium was assessed using the Pediatric Anesthesia Emergence Delirium Scale. Potential risk factors for PACU delirium were evaluated using multivariate logistic regression. Results: PACU delirium occurred in 245 (33%) of the 750 hemispheric procedures performed in 522 patients. Delirium was associated with a higher incidence in patients undergoing the first revascularization (37%) than in those undergoing the second (25%; P = 0.002). Cerebral infarction as the initial presentation (odds ratio [OR]: 4.64, first revascularization), high pediatric moyamoya magnetic resonance imaging (MRI) score (OR: 2.75, first revascularization; OR: 3.50, second revascularization), and high intraoperative mean arterial pressure variability (mmHg/min) (OR: 9.17, first revascularization; OR: 8.82, second revascularization) were associated with PACU delirium. Conversely, total intravenous anesthesia (TIVA) was associated with a lower incidence of PACU delirium (OR: 0.46, first revascularization; OR: 0.25, second revascularization). Conclusions A significant proportion of patients with MMD developed delirium in the PACU. High intraoperative blood pressure variability and preoperative MRI lesions are independent risk factors for PACU delirium in children with MMD. TIVA may exert a protective effect against PACU delirium. Further studies are required to clarify the causality of these associations.

BACKGROUND:Currently,there have been studies on three-dimensional digitalization and visualization systems for adult acupoints,but there are not many reports on the visualization of pediatric acupoints based on real pediatric digital sectional anatomical datasets. OBJECTIVE:To design and develop a digital three-dimensional visualization system for children's neck acupoints,to provide a basis for acupuncture and moxibustion,meridian and acupoint science teaching,clinical practice,acupuncture manipulation practice,and acupuncture safety research,and to provide a basis for the development of children's acupoint simulation system. METHODS:Based on a real cross-sectional anatomical dataset of pre-school boys,a three-dimensional digital virtual anatomical model of the neck region of children and internal multi-organ three-dimensional reconstruction were completed using PhotoShop 2021 and Digihuman Reconstruction System software.A database of 11 acupoints was compiled,including Fengfu and Fengchi,using the Unity database language.A three-dimensional model of children's neck anatomy,acupoint database,and writing acupuncture operation codes were integrated in Unity3D software.A three-dimensional digital visualization system for children's neck acupoints was successfully created,which integrated simulation acupoint positioning,three-dimensional acupoint anatomy,acupuncture training,clinical teaching,and acupuncture safety research. RESULTS AND CONCLUSION:(1)This study was based on real child specimens.Manual layer by layer segmentation of cross-sectional images was used to ensure the accuracy of the three-dimensional model to the greatest extent possible.The 3D software Digihuman Reconstruction System was utilized to extract and save independent segmentation data.PhotoShop 2021 software was collaborated with to complete dozens of three-dimensional reconstruction anatomical models of the outer skin of the neck and its internal bone structure,cervical spinal cord,blood vessels and nerves,muscles,and ligaments in children.The basic morphology and overall contour integrity verification of each independent structure were completed in MeshLab software.The 3-material research 13.0 software was applied for final fine tuning and anatomical position confirmation,successfully simulating and restoring the true anatomical morphology of the neck of preschool children.(2)Based on and referring to the national standards of the People's Republic of China,a database of commonly used acupoints in children's neck region was collected and organized,including their names,meridians,positioning,local anatomy,needle insertion levels,acupuncture methods,acupuncture accidents and prevention,acupoint indications,and two-dimensional anatomical sectional images.(3)Unity3D software was employed to integrate the three-dimensional model of children's neck,acupuncture simulation operation,and acupoint database,and a three-dimensional digital children's neck acupoint acupuncture visualization system was successfully constructed.The system displayed information on children's neck acupoints,two-dimensional and three-dimensional anatomical structures,and achieved two-dimensional and three-dimensional acupuncture simulation functions and acupuncture safety research functions for children's neck acupoints.Based on the ultra-thin sectional anatomical dataset of real child specimens,the first three-dimensional digital and visualization system for acupoints in the neck region of children had been constructed.Compared with previous acupoint acupuncture systems,it is more in line with the anatomical and morphological development characteristics of Asian children and has high application value in the fields of acupuncture safety research,clinical teaching,and acupuncture simulation training.

ObjectiveTo investigate the potential mechanism of action of the Qufeng Tongqiao Cough-relieving Decoction （祛风通窍止咳方， QTCD） in the treatment of upper airway cough syndrome （UACS）. MethodsTwenty-four guinea pigs were randomly divided into blank group， model group， traditional Chinese medicine （TCM） group， and inhibitor group， with six guinea pigs in each group. Except for the blank group， guinea pigs were sensitized with ovalbumin and aluminum hydroxide via intraperitoneal injection， followed by ovalbumin nasal drops combined with smoke exposure to establish the UACS model. After modeling， the TCM group was administered QTCD 0.9 g/（100 g·d） by gavage， the inhibitor group received the transient receptor potential vanilloid receptor 4 （TRPV4） inhibitor GSK2193874 1 mmol/L， 5 min by nebulisation， and the blank group and model group were given 2 ml/（100 g·d） normal saline by gavage once daily. After 7 days of treatment， a cough provocation test was performed using 0.4 mol/L citric acid. The levels of IgE in serum and inflammatory cytokines， including interleukin-6 （IL-6）， interleukin-8 （IL-8） in serum， bronchoalveolar lavage fluid （BALF）， and nasal lavage fluid （NLF） were detected by enzyme-linked immunosorbent assay （ELISA）. Histopathological changes in lung and nasal mucosal tissues were observed by hematoxylin-eosin （HE） staining. Immunohistochemistry was used to detect the protein levels of TRPV4， substance P （SP）， and calcitonin gene-related peptide （CGRP） in lung and nasal mucosal tissues. Real-time polymerase chain reaction （Real-time PCR） was used to detect the mRNA expression of TRPV4， SP， and CGRP in lung tissues. ResultsHE staining showed significant structural damage and infiltration of inflammatory cells in the lung and nasal mucosal tissues in the model group， while the TCM group and inhibitor group showed improved pathological changes. Compared with the blank group， the model group showed increased cough frequency， serum IgE level， and IL-6 and IL-8 levels in serum， BALF， and NLF. The protein levels of TRPV4， SP， and CGRP in lung and nasal mucosal tissues and their mRNA expression were elevated （P＜0.05 or P＜0.01）. Compared with the model group， the TCM group and inhibitor group showed reduced cough frequency， serum IgE level， and TRPV4 and SP mRNA expression in lung tissues. The TCM group showed reduced IL-6 and IL-8 levels in serum， BALF， and NLF， and reduced TRPV4 and CGRP protein levels in lung and nasal mucosal tissues. The inhibitor group showed reduced IL-6 and IL-8 levels in serum， BALF， and NLF， reduced IL-6 in BALF， reduced IL-8 in NLF， and decreased TRPV4， SP， and CGRP protein levels in lung tissues and SP and CGRP protein levels in nasal mucosal tissues （P＜0.05 or P＜0.01）. Compared with the TCM group， the inhibitor group had increased serum IgE， IL-6， and IL-8 levels， increased IL-6 level in BALF， and increased IL-8 levle in NLF， but decreased SP protein level in lung tissues and increased TRPV4 and SP mRNA expression in lung tissues （P＜0.01）. ConclusionQTCD effectively reduces cough frequency in the UACS guinea pig model. Its mechanism may involve inhibiting the activation of the TRPV4 pathway， improving airway neurogenic inflammation， alleviating inflammatory responses， and reducing cough hypersensitivity.