Objective: To characterize perioperative dynamic changes in immune-cell phenotypes and inflammatory cytokines in patients undergoing CPB (cardiopulmonary bypass) cardiac surgery, and to explore their associations with postoperative outcomes. Methods: In this prospective cohort study, 120 adult patients who underwent elective cardiac surgery under CPB at West China Hospital from May 2022 to March 2023 were enrolled. Perioperative immune-cell phenotypes and concentrations of 40 inflammation-related cytokines were measured. The primary outcomes were the sequential organ failure assessment (SOFA) score at 24 h after surgery and ΔSOFA (the peak SOFA score within 48 h after surgery minus the preoperative SOFA score). Secondary outcomes included major adverse cardiovascular events (MACE), acute kidney injury (AKI), respiratory failure, severe liver injury, and infection. Results: The mean age of enrolled patients was 57±10 years. Of these, 52% (62/120) were male and 90% (108/120) underwent valve surgery. During the rewarming to the end of CPB, neutrophil counts rapidly increased (7.39×10 /L vs preoperative 3.07×10 /L, P<0.001), with significant upregulation of CD11b (7.30×10 /L vs preoperative 3.05×10 /L, P<0.001) and CD54 (7.15×10 /L vs preoperative 2.99×10 /L, P<0.001). Lymphocyte counts increased at the end of CPB (1.75×10 /L vs preoperative 1.12×10 /L, P<0.001) but decreased significantly at 24 h after surgery (0.59×10 /L vs preoperative 1.12×10 /L, P<0.001). Plasma analysis showed that multiple pro-inflammatory cytokines increased during CPB and remained elevated up to 24 h after surgery; five chemokines and the anti-inflammatory cytokine IL-10 peaked at the end of CPB. The SOFA score increased from 1 (1, 2) preoperatively to 7 (5, 10) at 24 h after surgery, with a ΔSOFA of 6 (4, 8). Within 30 days after surgery, 48 patients (40.0%) developed AKI, 17 (14.2%) developed infection, 4 (3.3%) developed severe liver injury, 3 (2.5%) developed respiratory failure, and 3 (2.5%) experienced MACE. During the 2-year follow-up, 8 patients (6.7%) experienced MACE and 5 (4.2%) died. Conclusion: Multi-organ dysfunction is common after cardiac surgery under CPB (median ΔSOFA, 6), accompanied by perioperative activation of multiple immune-cell subsets and upregulation of pro-inflammatory, anti-inflammatory, and chemotactic mediators. This study provides data-driven evidence and research clues for further investigation of the associations between CPB-related immune perturbations and postoperative organ dysfunction and clinical outcomes.

Against the backdrop of digital transformation in higher education， the traditional teaching model has become inadequate to meet the demands for cultivating new-quality nursing talents. Nursing ethics teaching confronts several dilemmas， such as unbalanced regional development， disconnection between theory and practice， scattered teaching resources， and fragmented knowledge points. With the iterative update of modern digital technologies， the knowledge graph， due to its structured， semantic， scalable， and multi-source integrative characteristics， offers a technological pathway to address these issues. Based on the construction foundation of the Ministry of Education’s first batch of virtual teaching and research platforms for humanistic nursing courses， the nursing ethics artificial intelligence（Al）course was developed around the“thinking-research-teaching-learning”framework. By strengthening ideological and political guidance， constructing a curriculum knowledge graph， and promoting the deep integration of humanistic care and professional knowledge，the course realized intelligent support for research，learning，and teaching. This innovative education model provides a replicable paradigm for cultivating outstanding nursing talents equipped with humanistic literacy， digital competence， and advanced ethical thinking， while also offering references for the digital transformation of higher nursing education.

ObjectiveTo investigate the value of preoperative dual-layer spectral detector CT （DLCT） parameters in predicting lymph node metastasis （LNM） of non-functional pancreatic neuroendocrine neoplasms （NF-pNENs）. MethodsA retrospective study was conducted on patients with pathologically confirmed NF-pNENs who underwent preoperative contrast-enhanced DLCT examination between September 2019 and July 2024. Regions of interest （ROIs） were manually delineated on three representative slices of the solid component of the lesion， and the mean values were recorded. Conventional CT parameters， monochromatic energy images （40 keV， 70 keV， 100 keV）， iodine concentration maps， and effective atomic number （Z_eff） maps in the pancreatic parenchymal phase and portal venous phase were acquired. A total of 34 parameters， including clinical characteristics， imaging features， conventional CT and DLCT quantitative parameters， were analyzed. Intergroup differences were compared between the LNM and non-LNM groups. Independent predictive factors were screened using logistic regression and least absolute shrinkage and selection operator （LASSO） regression. Receiver operating characteristic （ROC） curves were generated for each predictive model， and the area under the curve （AUC） was calculated to evaluate the predictive efficacy. ResultsA total of 82 patients with NF-pNENs were enrolled， including 37 males and 45 females， with a mean age of 49.7±14.7 years. Thirty patients were performed with LNM and 52 were with non-LNM. After univariate logistic regression， LASSO regression and multivariate stepwise logistic regression analyses， body mass index （BMI）， organ invasion， normalized CT value in the portal venous phase （nCTv） and normalized iodine concentration in the portal venous phase （nICv） were identified as independent predictive factors. The AUCs of the clinical-radiological qualitative model （BMI+organ invasion）， conventional CT model （nCTv）， DLCT model （nICv） and comprehensive model （organ invasion+nICv） were 0.815 （0.719， 0.910）， 0.750 （0.642， 0.858）， 0.829 （0.733， 0.925） and 0.865 （0.879， 0.953）， respectively. The comprehensive model combining clinical-radiological and DLCT characteristics exhibited superior predictive performance. ConclusionDLCT parameters are more effective than conventional CT parameters in predicting LNM in NF-pNENs， enabling non-invasive preoperative prediction and assisting clinical decision-making.

ObjectiveTo investigate the value of preoperative dual-layer spectral detector CT （DLCT） parameters in predicting lymph node metastasis （LNM） of non-functional pancreatic neuroendocrine neoplasms （NF-pNENs）. MethodsA retrospective study was conducted on patients with pathologically confirmed NF-pNENs who underwent preoperative contrast-enhanced DLCT examination between September 2019 and July 2024. Regions of interest （ROIs） were manually delineated on three representative slices of the solid component of the lesion， and the mean values were recorded. Conventional CT parameters， monochromatic energy images （40 keV， 70 keV， 100 keV）， iodine concentration maps， and effective atomic number （Z_eff） maps in the pancreatic parenchymal phase and portal venous phase were acquired. A total of 34 parameters， including clinical characteristics， imaging features， conventional CT and DLCT quantitative parameters， were analyzed. Intergroup differences were compared between the LNM and non-LNM groups. Independent predictive factors were screened using logistic regression and least absolute shrinkage and selection operator （LASSO） regression. Receiver operating characteristic （ROC） curves were generated for each predictive model， and the area under the curve （AUC） was calculated to evaluate the predictive efficacy. ResultsA total of 82 patients with NF-pNENs were enrolled， including 37 males and 45 females， with a mean age of 49.7±14.7 years. Thirty patients were performed with LNM and 52 were with non-LNM. After univariate logistic regression， LASSO regression and multivariate stepwise logistic regression analyses， body mass index （BMI）， organ invasion， normalized CT value in the portal venous phase （nCTv） and normalized iodine concentration in the portal venous phase （nICv） were identified as independent predictive factors. The AUCs of the clinical-radiological qualitative model （BMI+organ invasion）， conventional CT model （nCTv）， DLCT model （nICv） and comprehensive model （organ invasion+nICv） were 0.815 （0.719， 0.910）， 0.750 （0.642， 0.858）， 0.829 （0.733， 0.925） and 0.865 （0.879， 0.953）， respectively. The comprehensive model combining clinical-radiological and DLCT characteristics exhibited superior predictive performance. ConclusionDLCT parameters are more effective than conventional CT parameters in predicting LNM in NF-pNENs， enabling non-invasive preoperative prediction and assisting clinical decision-making.

Objective:To explore the association between the systemic immune-inflammation index (SII) and obesity metabolic phenotypes, as well as metabolic features in children and adolescents.Methods:A cross-sectional study was conducted using the random cluster sampling method from March 2023 to May 2024. Children and adolescents aged 9-17 years in Guangzhou were surveyed through questionnaires, physical measurements, and blood tests. According to BMI and metabolic status, participants were classified into normal-weight groups [metabolically healthy normal weight (MHNW) and metabolically unhealthy normal weight (MUNW)] and overweight/obese groups [metabolically healthy overweight/obese (MHO/O) and metabolically unhealthy overweight/obese (MUO/O)]. After natural log-transformation of SII values (lnSII), multinomial logistic regression was used to assess the association between SII and obesity metabolic phenotypes, while binary logistic regression was applied to assess the relationship between SII and metabolic phenotypes in the overweight/obese subgroup. Linear regression model and restricted cubic spline (RCS) were employed to examine the relationship between SII and metabolic features among the entire population.Results:A total of 3 749 participants were included. After adjusting for covariates, for every unit increase in lnSII, the risk of MHO/O and MUO/O increased by 93% ( OR=1.93, 95% CI: 1.56-2.40, P<0.001) and 156% ( OR=2.56, 95% CI: 2.02-3.25, P<0.001), respectively. In the overweight/obesity subgroup, for every unit increase in lnSII, the risk of MUO/O increased by 37% ( OR=1.37, 95% CI: 1.01-1.87, P=0.045). Linear regression model and RCS showed that lnSII was positively correlated with systolic blood pressure (SBP) and diastolic blood pressure (DBP) (SBP: β=1.39, 95% CI: 0.67-2.11, P<0.001; DBP: β=1.27, 95% CI: 0.79-1.75, P<0.001). lnSII also had a non-linear relationship with triglyceride ( Pnonlinear=0.032) and high-density lipoprotein cholesterol ( Pnonlinear=0.002). Conclusion:Elevated SII levels are associated with unfavorable obesity metabolic phenotypes, higher blood pressure, and altered lipid profiles in children and adolescents. SII may be a potential driving factor for metabolic heterogeneity in children and adolescents.

Objective To explore and analyze adverse drug events(ADE)signals of azithromycin,identify common adverse events and suspected adverse reactions that occur easily in the real clinical application of azithromycin.Methods The adverse drug event reports related to azithromycin recorded in the US FDA Adverse Event Reporting System database from October 1,2003,to October 1,2023,were mined using the OpenVigil 2.1 drug surveillance platform.Signal detection and analysis were carried out using the reporting odds ratio(ROR)and Bayesian confidence propagation neural network method(BCPNN).Results A total of 5498 ADE signals were identified,with a total of 112485 reports.Eventually,31,041 azithromycin-associated adverse event reports were extracted,involving 898 positive signals,27 system organ classes,mainly concentrated in respiratory system diseases,infections,gastrointestinal system diseases,and others.Additionally,some adverse reactions possibly caused by azithromycin were discovered,such as asthma,wheezing,and potential reactions like incomplete abortion.Conclusion When using azithromycin,besides paying attention to the adverse reactions listed in the drug instructions,we should also pay attention to some adverse reactions that have not been timely recorded or updated,in order to prevent the medication safety risks caused by outdated instructions,provide reasonable medication advice,and ensure the medication safety of patients.

Objective: To investigate the iodine nutrition status of children aged 8-10 in Guangming, Longhua and Yantian District of Shenzhen in 2023, and to explore the influencing factors of thyroid volume. To evaluate prevention strategies and to provide a scientific basis for the elimination of iodine deficiency disorders. Methods: Urine and household salt samples were randomly collected from 580 non-boarding students aged 8-10 years foriodine content detection. Thyroid volume was measured using a fully digital ultrasound imaging system, and goiter prevalence was calculated. Results: A total of 580 samples was tested. The median salt iodine concentration was 23.86 mg/kg, with 93.62% qualified iodized salt and 94.48% coverage rate. The median of urinary iodine was 265.00 μg/L, mainly distributed between 200 - < 300 μg/L and ≥300 μg/L. The proportion of children with ap⁃ propriate iodine was 20. 86% , and the proportion of children with insufficient or excessive urinary iodine levels was 10. 86% and 68. 28% of the total surveyed population , respectively. The median thyroid volume was 3. 27 mL , and the goiter rate was 1. 72% . Multiple linear regression analysis showed that age was the risk factor for thyroid volume (8=0 328, P<0.05). while urinary iodine was the protective factor for thyroid volume(B=-4.134x10-4,P<0.05). Conclusion The qualified iodized salt rate, median of urinary iodine,and goiter prevalence of 580 children aged 8 - 10 meet the elimination criteria for iodine deficiency disorders. Age and urinary iodine are closely related to thyroid volume change. The urinary iodine level of children is generally high and requires serious attention.

Objective:To analyze the current situation of health-related quality of life (HRQOL) and its influencing factors among community-dwelling elderly with mild cognitive impairment (MCI) based on the health ecology model (HEM).Methods:From December 2023 to September 2024, a cross-sectional survey was conducted among 997 community-dwelling elderly in Beijing, Shandong, Chongqing and other regions. The EuroQol five-dimensional questionnaire 5 level (EQ-5D-5L), the Montreal cognitive assessment (MoCA), and the Pittsburgh sleep quality index (PSQI) were used to assess the subjects.Descriptive analysis, Mann-Whitney U test, Kruskal-Wallis test, and Tobit regression analysis were performed using Stata 18.0 software. Results:A total of 324 valid samples were finally obtained, and the health utility value of MCI elderly was 0.842(0.815, 0.951). Tobit regression analysis showed that ≥80 years old( β=-0.121, 95% CI=-0.193--0.050) in individual traits level, don't exercise( β=-0.196, 95% CI=-0.255--0.137) and poor quality of sleep ( β=-0.064, 95% CI=-0.116--0.013) in behavior characteristics level, and poor subjective economic status( β=-0.153, 95% CI=-0.261--0.045) in living and working conditions level were risk factors for the health utility value of the elderly with MCI. Drinking( β=0.096, 95% CI=0.022-0.171) in behavior characteristics level and participating in social activities( β=0.126, 95% CI=0.062-0.190) in interpersonal network level were protective factors for the health utility value of the elderly with MCI. Conclusions:The HRQOL of the community-dwelling elderly with MCI in China is low, and its influencing factors are multi-level. HEM should be combined to strengthen the intervention and management of the elderly with MCI from personal constitution to policy environment to improve their HRQOL.

Objective:To investigate the value of MULTI-parametric MR imaging with flexible design (MTP) combined with microview diffusion weighted imaging (DWI) in predicting pituitary tumor invasion of cavernous sinus.Methods:This was a cross-sectional study. The clinicopathological and imaging data of 59 patients with suspected pituitary tumor who were admitted to the First Affiliated Hospital of Dalian Medical University from December 2021 to August 2024 were prospectively analyzed. According to Knosp classification, patients with pituitary tumor were divided into non-invasive group (28 cases) and invasive group (31 cases). All patients underwent MTP and microview DWI sequence scanning, and the corresponding parameter values [T 1, R 2*, T 2* and apparent diffusion coefficient (ADC)] were measured on the MTP quantitative map and ADC map at the maximum diameter level of the pituitary tumor. Independent sample t test and Mann-Whitney U test were used to compare the clinical data, quantitative parameter values and proliferation index (Ki-67) between the non-invasive group and the invasive group. Quantitative parameter values with statistically significant differences were jointly included in logistic regression to construct the model. Receiver characteristic curve and area under the curve (AUC) were used to analyze single variables and logistic model in predicting the value invasion of pituitary tumor cavernous sinus invasion. Spearman correlation was used to analyze the correlation between the quantitative values and Ki-67 level. Results:There was no significant difference in age and gender between the non-invasive group and the invasive group ( P>0.05). T 1 and T 2* values in invasion group were higher than those in non-invasion group ( Z=4.42, P<0.001; Z=3.43, P<0.001), R 2* values and ADC values in the invasion group were lower than those in the non-invasion group, and the difference was statistically significant (t=4.07, P<0.001; Z=-3.07, P=0.002). The AUC values of T 1, R 2*, T 2*, ADC, logistic model 1(T 1+R 2*+ADC) and logistic model 2(T 1+T 2*+ADC) for predicting pituitary tumor cavernous sinus invasion were 0.835, 0.767, 0.760, 0.733, 0.926 and 0.925, respectively. Correlation analysis showed that the value of pituitary tumor T 1 was positively correlated with Ki-67 ( r=0.431, P=0.002). Conclusion:Quantitative parameters of MTP sequence and microview DWI sequence can quantitatively evaluate pituitary tumor invasion of cavernous sinus, and the combination of the two sequences can significantly improve the prediction efficiency.

Objective:To explore the application value of radiomics models based on MRI of vertebrae and paravertebral muscles in identifying potential vertebral fragility fracture risk in osteoporosis and osteopenia.Methods:This cross-sectional study collected data from patients who underwent both dual-energy X-ray absorptiometry (DXA) and lumbar MRI at the Third Affiliated Hospital of Southern Medical University between January 2014 and December 2023,retrospectively. Based on DXA results, patients were categorized into osteoporosis group ( n=302) and osteopenia group ( n=264), with fracture and non-fracture patients matched at 1∶1 ratio by propensity score matching based on age, gender, and body mass index. The fourth lumbar vertebra was selected as the region of interest (ROI) for the vertebral body, and the bilateral psoas major, erector spinae, and multifidus muscles were selected as the ROIs for the paraspinal muscles. A total of 7 259 radiomics features were extracted from these ROIs. The dataset was divided into a training set and a test set in an 8∶2 ratio by simple random sampling (osteoporosis group 241 and 61 cases, osteopenia group 211 and 53 cases). The T-score was used to establish the clinical model. After feature normalization and dimensionality reduction, logistic regression was applied to build three radiomics models: vertebral model, paraspinal muscle model, and vertebral-paraspinal muscle model. The T-score was then combined with the radiomics model that achieved the highest area under the receiver operating characteristic curve (AUC) in the test set to construct a clinical-radiomics combined model. Model performance was evaluated using the AUC. The DeLong test was used to compare the diagnostic efficacy between models. Results:In the test set, the vertebral-paravertebral muscle model achieved the highest AUC among radiomics models and was selected for combination with the T-score. In identifying potential vertebral fragility fractures of osteoporosis group, the AUC (95% CI) of the clinical model, vertebral model, paraspinal muscle model, vertebral-paraspinal muscle model, and clinical-radiomics model were 0.523 (0.373-0.672), 0.869 (0.779-0.959), 0.608 (0.464-0.752), 0.876 (0.791-0.961), and 0.860 (0.769-0.952), respectively. For osteopenia group, the corresponding AUC(95% CI) were 0.625 (0.467-0.783), 0.696 (0.547-0.845), 0.706 (0.563-0.848), 0.816 (0.702-0.930), and 0.820 (0.710-0.930). The DeLong test showed that the vertebral model for identifying the potential vertebral fracture risk in osteoporosis group had better performance than the paraspinal muscle model ( Z=3.28, P=0.001). While for osteopenia group, there was no significant difference in diagnostic performance between the vertebral model and the paraspinal muscle model ( Z=0.09, P=0.932). The recognition efficacy of the clinical model and the vertebral-paraspinal muscle model was significantly different ( Z=3.69, 1.98; P<0.001, P=0.047), while there was no significant difference between the clinical-radiomics combined model and the vertebral-paraspinal muscle model ( Z=1.51, 0.12; P=0.131, 0.904). Conclusion:The MRI-based vertebral-paraspinal muscle radiomics model can effectively identify osteoporosis or osteopenia patients with potential fragility fracture risk. In osteopenia group, the efficacy of the MRI radiomics models based on the vertebra and paraspinal muscles in identifying potential vertebral fragility fracture risk is comparable.