AIM:To investigating the predictive value of serum delta-like ligand 4(DLL4), complement C1q/tumor necrosis factor-related protein 5(CTRP5)levels for the severity of diabetic retinopathy(DR)and visual disability.METHODS:Patients with DR admitted to Tangshan Central Hospital between January 2022 and January 2024 were enrolled. Based on disease severity, patients were divided into a proliferative DR group and a non-proliferative DR group. After one year of follow-up, patients were further categorized into a vision disability group and a non-visual disability group based on visual impairment status. Enzyme-linked immunosorbent assay(ELISA)was used to detect serum levels of DLL4 and CTRP5. The data and serum levels of DLL4 and CTRP5 were compared among patients with different medical conditions and visual disabilities. Pearson method was used to explore the correlation between serum levels of DLL4, CTRP5 and glucose and lipid metabolism indicators. Multivariate Logistic regression was performed to explore the influencing factors of visual disability in DR Receiver operating characteristic(ROC)curve was performed to explore the value of serum levels of DLL4 and CTRP5 in predicting visual disability in DR.RESULTS: This study included 245 DR patients.Ninety-five patients were in the proliferative DR group(mean age 51.61±3.44 y, 51 men and 44 women), and 150 patients were in the non-proliferative DR group(mean age 51.22±3.11 y, 86 men and 64 women). The visually disability group consisted of 39 participants(mean age 51.64±3.87 y; 21 men and 18 women), while the non-visually disability group consisted of 206 participants(mean age 51.32±3.12 y; 116 men and 90 women). Patients in the proliferative DR group exhibited longer DR duration, higher levels of FPG, TG, TC, LDL-C, and serum DLL4 and CTRP5, and lower HDL-C levels compared to the non-proliferative DR group(all P<0.05). The serum levels of DLL4 were positively correlated with FPG(P<0.001), while the serum levels of CTRP5 were prominently positively correlated with FPG, TG, TC, LDL-C, and prominently negatively correlated with HDL-C(all P<0.001). The visual disability group had longer duration of DR and higher serum levels of DLL4 and CTRP5 than the non-visual disability group(all P<0.001). The duration of DR and serum levels of DLL4 and CTRP5 were influencing factors for visual disability in DR patients(all P<0.001). The joint detection of serum levels of DLL4 and CTRP5 had a higher value in predicting visual disability in DR patients than the single indicator prediction(ZDLL4-joint=3.018, PDLL4-joint=0.003; ZCTRP5-joint=2.784, PCTRP5-joint=0.005). CONCLUSION: Serum levels of DLL4 and CTRP5 are elevated in DR patients, and are closely related to the disease condition. The joint detection of serum levels of DLL4 and CTRP5 has high value in predicting visual disability in DR patients.

Objectives:To investigate the distribution and change of the burden of cardiovascular diseases attributable to tobacco consumption in China and the world from 1990 to 2021.Methods:Based on Global Burden of Disease(GBD)2021 database,age standardized mortality and age standardized disability-adjusted life year(DALY)rates and estimated annual percentage change(EAPC)from cardiovascular disease(including ischemic heart disease,stroke,atrial fibrillation and flutter,aortic aneurysm,peripheral artery disease)attributable to tobacco consumption were analyzed.The association of the human development index(HDI)and social demographic index(SDI)with age-standardized mortality was also analyzed.Results:Compared to 1990,the global burden of cardiovascular diseases attributable to smoking declined in 2021,age-standardized mortality decreased from 57.2/100 000 to 26.3/100 000(EAPC=-1.81%,95% CI:-2.00% to-1.63% ).The global burden of cardiovascular diseases attributable to second-hand smoke also decreased,age-standardized mortality decreased from 11.4/100 000 to 8.3/100 000(EAPC=-1.72%,95% CI:-1.91% to-1.53% ).In China,the burden of cardiovascular diseases attributable to smoking also decreased,age-standardized mortality decreased from 52.2/100 000 to 39.6/100 000(EAPC=-1.23%,95% CI:-1.44%-1.02% );the burden of cardiovascular diseases attributable to second-hand smoke decreased,age-standardized mortality decreased from 15.3/100 000 to 14.7/100 000(EAPC=-1.26%,95% CI:-1.63% to-0.90% ).Notably,the decrease in cardiovascular diseases burden attributable to second-hand smoke among Chinese women was more significant than the global level,the age-standardized mortality rate of Chinese women decreased from 17.9/100 000 to 14.5/100 000(EAPC=-2.24%,95% CI=-2.78%～-1.86% ).Among the five types of cardiovascular diseases attributable to tobacco consumption globally and in China,the age-standardized mortality and age-standardized DALY rates of aortic aneurysm,ischemic heart disease and peripheral artery disease were higher.Globally,ischaemic heart disease is the leading cause of death,accounting for 60.2% in 1990 and 61.7% in 2021,while stroke is the leading cause of death in China,accounting for 68.1% and 51.4% in 1990 and 2021,respectively.In addition,HDI and SDI are the two main factors affecting the disease burden.In regions and countries with SDI>7.2,age standardized mortality is below our forecast line.In the later part of the forecast,China's age standardized mortality showed a downward trend,possibly due to changes in tobacco control measures.Conclusions:Over the past 30 years,the burden of cardiovascular diseases attributed to tobacco consumption has decreased globally and in China.The decline in disease burden has been most pronounced among women.However,in countries and regions with an SDI below 7.2,the burden of disease remains significant high.Therefore,it is necessary to take tobacco control measures in key regions(China,East Asia,Central Europe,Central Asia and Southeast Asia)to actively reduce smoking rates and exposure to secondhand smoke in public places,so as to reduce the burden of cardiovascular diseases.

Theory and technology of Medical Immunology are widely used in scientific research.Our teaching and research group uses experimental teaching of Medical Immunology as a platform to carry out practice of scientific research project-based experi-mental system among"5+3"integration students.By completing a mini-project research including experimental design-experimental operation-research article writing,students cultivated scientific research thinking and exercised scientific research practice ability,and generally reported that the course is very difficult,but after completing it,it is very rewarding.

Objective To analyze the factors influencing iodine nutritional status in pregnant women dur-ing pregnancy,based on thyroid function and thyroid autoantibody levels,and to explore the association between iodine nutritional abnormalities and pregnancy outcomes.Methods A total of 838 pregnant women who underwent routine prenatal checkups at Qinghai Provincial People's Hospital between January 2021 and June 2023 were pro-spectively enrolled in this study.All participants were followed until delivery.Seven cases were lost to follow-up,resulting in a final sample size of 831 participants.Among them,276 were in the first trimester,384 in the second trimester,and 171 in the third trimester.Data on urinary iodine concentration(UIC),urinary creatinine(UCr),thyroid function indicators,and thyroid autoantibodies were collected.Based on their iodine nutritional status,the participants were categorized into either the iodine-sufficient group or the iodine-abnormal group(including iodine-deficient,iodine-hyper-sufficient,and iodine-excessive subgroups).This study analyzed the iodine nutritional sta-tus of pregnant women during different gestational periods,compared thyroid function indices,prevalence of thy-roid diseases,and the positivity rates of thyroid peroxidase antibody(TPOAb),thyroglobulin antibody(TGAb),and thyroid-stimulating hormone receptor antibody(TRAb)among different iodine status groups.Additionally,ad-verse pregnancy outcomes were compared across groups.Multivariate logistic regression analysis was conducted to identify risk factors associated with iodine abnormalities during pregnancy,and a predictive model was developed to assess its potential predictive value.Results Among the 831 pregnant women included in the study,373 cases(44.89％)exhibited iodine sufficiency,while 458 cases(55.11％)presented with iodine abnormalities,including 282 cases of iodine deficiency,144 cases of iodine hypersufficiency,and 32 cases of iodine excess.No statistically significant differences were observed in the iodine nutritional status across different trimesters(P>0.05).The se-rum level of thyroid-stimulating hormone(TSH)was significantly higher in the iodine abnormal group compared to the iodine sufficient group(P<0.05).Additionally,the iodine abnormal group demonstrated higher positivity rates of TPOAb alone,TGAb,and TRAb,as well as increased incidence of thyroid dysfunction and total adverse pregnancy outcomes compared to the iodine sufficient group(all P<0.05).These adverse indicators were also sig-nificantly elevated in the iodine-deficient,iodine super-sufficient,and iodine overdose subgroups compared to the iodine sufficient group(P<0.05).Elevated serum TSH levels and the presence of TPOAb,TGAb,and TRAb were identified as risk factors for iodine abnormalities during pregnancy(P<0.05).The predictive model con-structed for identifying iodine abnormalities in pregnant women demonstrated an area under the curve(AUC)of 0.876,with a sensitivity of 72.27％and a specificity of 89.01％.Conclusions The prevalence of iodine nutritional abnormalities among pregnant women during pregnancy was high,with most cases presenting iodine deficiency.These abnormalities were associated with thyroid function,thyroid autoimmunity,and pregnancy outcomes,but showed no significant correlation with gestational age.Furthermore,the prediction model developed based on iden-tified risk factors demonstrated effective performance in predicting iodine nutritional abnormalities during preg-nancy.

Objective To analyze the factors influencing iodine nutritional status in pregnant women dur-ing pregnancy,based on thyroid function and thyroid autoantibody levels,and to explore the association between iodine nutritional abnormalities and pregnancy outcomes.Methods A total of 838 pregnant women who underwent routine prenatal checkups at Qinghai Provincial People's Hospital between January 2021 and June 2023 were pro-spectively enrolled in this study.All participants were followed until delivery.Seven cases were lost to follow-up,resulting in a final sample size of 831 participants.Among them,276 were in the first trimester,384 in the second trimester,and 171 in the third trimester.Data on urinary iodine concentration(UIC),urinary creatinine(UCr),thyroid function indicators,and thyroid autoantibodies were collected.Based on their iodine nutritional status,the participants were categorized into either the iodine-sufficient group or the iodine-abnormal group(including iodine-deficient,iodine-hyper-sufficient,and iodine-excessive subgroups).This study analyzed the iodine nutritional sta-tus of pregnant women during different gestational periods,compared thyroid function indices,prevalence of thy-roid diseases,and the positivity rates of thyroid peroxidase antibody(TPOAb),thyroglobulin antibody(TGAb),and thyroid-stimulating hormone receptor antibody(TRAb)among different iodine status groups.Additionally,ad-verse pregnancy outcomes were compared across groups.Multivariate logistic regression analysis was conducted to identify risk factors associated with iodine abnormalities during pregnancy,and a predictive model was developed to assess its potential predictive value.Results Among the 831 pregnant women included in the study,373 cases(44.89％)exhibited iodine sufficiency,while 458 cases(55.11％)presented with iodine abnormalities,including 282 cases of iodine deficiency,144 cases of iodine hypersufficiency,and 32 cases of iodine excess.No statistically significant differences were observed in the iodine nutritional status across different trimesters(P>0.05).The se-rum level of thyroid-stimulating hormone(TSH)was significantly higher in the iodine abnormal group compared to the iodine sufficient group(P<0.05).Additionally,the iodine abnormal group demonstrated higher positivity rates of TPOAb alone,TGAb,and TRAb,as well as increased incidence of thyroid dysfunction and total adverse pregnancy outcomes compared to the iodine sufficient group(all P<0.05).These adverse indicators were also sig-nificantly elevated in the iodine-deficient,iodine super-sufficient,and iodine overdose subgroups compared to the iodine sufficient group(P<0.05).Elevated serum TSH levels and the presence of TPOAb,TGAb,and TRAb were identified as risk factors for iodine abnormalities during pregnancy(P<0.05).The predictive model con-structed for identifying iodine abnormalities in pregnant women demonstrated an area under the curve(AUC)of 0.876,with a sensitivity of 72.27％and a specificity of 89.01％.Conclusions The prevalence of iodine nutritional abnormalities among pregnant women during pregnancy was high,with most cases presenting iodine deficiency.These abnormalities were associated with thyroid function,thyroid autoimmunity,and pregnancy outcomes,but showed no significant correlation with gestational age.Furthermore,the prediction model developed based on iden-tified risk factors demonstrated effective performance in predicting iodine nutritional abnormalities during preg-nancy.

Objective:To conduct a comprehensive global review of research on toxic leadership behavior among nursing managers and to analyze the current research status.Methods:Literature related to toxic leadership behavior among nursing managers was retrieved from PubMed, Web of Science, Cochrane Library, China National Knowledge Infrastructure, Wanfang Database, VIP Chinese Science and Technology Journal Database, and China Biomedical Literature Database. The search period extended from the inception of each database to February 15, 2025. The included literature was then organized, analyzed, and summarized.Results:A total of 28 studies were included. There were 23 studies reported the occurrence of toxic leadership behavior among nursing managers, the incidence of toxic leadership behavior was almost at a moderately low level. There were 8 studies reported the influencing factors of toxic leadership behavior, its influencing factors encompassed three primary aspects: the organizational level, the personal characteristics of nursing managers, and characteristics of the nursing staff group. Assessment tools of toxic leadership behavior included the Toxic Leadership Behaviors of Nurse Managers, the Abuse Management Questionnaire, etc. The adverse consequences included increased nurse turnover intention, decreased nursing quality, and reduced organizational trust, etc. Interventions were planned and implemented from three perspectives: the hospital managers, nursing managers, and the nurses.Conclusions:The factors influencing toxic leadership behavior among nursing managers and its adverse consequences require further exploration. Therefore, more intervention studies are warranted to provide new insights and methods for preventing and reducing toxic leadership behavior.

Generative artificial intelligence technologies, represented by large language models, are poised to impact educational ecosystems comprehensively. This article focuses on the nursing education field, first introducing the basic concepts and evolution of large language models. It then outlines typical applications of this technology in enabling innovative practices in nursing education, showcasing its immense potential in reshaping content generation methods, teaching models, educational settings, and evaluation systems. Additionally, the article analyzes key challenges that may arise, including inadequate professional construction, alienation in teacher-student relationships, over-reliance on digital tools, and unequal access to technology. By examining the frontier applications and potential risks of large language models in nursing education, this work aims to inspire ideas and provide references for the digital transformation of nursing education.

Objective To investigate the clinical characteristics and related risk factors of severe Mycoplasmal pneumoniae pneumonia(SMPP)in children.Methods Analysis of clinical data of 240 children with Mycoplasmal pneumoniae pneumonia admitted to Guangxi Hospital Division of the First Affiliated Hospital,Sun Yat-sen University from October 2023 to March 2024.According to the severity of the disease,they were divided into SMPP group and general Mycoplasmal pneumoniae pneumonia(GMPP)group,multivariate Logistic regression analysis was used to analyze the risk factors related to the occurrence of SMPP.The receiver operating characteristic(ROC)curve was plotted to analyze the predictive value of each independent risk factor of SMPP.Results Compared the data during hospitalisation between GMPP group and SMPP group,the SMPP group had longer fever course,hospitalization time,azithromycin treatment time,and glucocorticoid use time(P＜0.05).The proportion of patients with unilateral lung lesions and large patchy shadows in SMPP group were significantly higher than those in GMPP group(P＜0.05).The levels of C-reactive protein,interleukin(IL)-6,and D-dimer in SMPP group were significantly higher than those in GMPP group,while the peripheral blood lymphocyte count was significantly lower than that in GMPP group(P＜0.05).The results of multiple Logistic regression analysis showed that the duration of fever,D-dimer,IL-6,and large patchy shadows in the lungs were independent risk factors for SMPP.The ROC curve results showed that fever duration ≥ 6.5 days,D-dimer≥0.495mg/L,IL-6≥11.05pg/ml,and large patchy shadows in the lungs had good application value in distinguishing SMPP and GMPP children.Conclusion Prolonged fever duration(≥6.5 days),significantly elevated levels of D-dimer and IL-6,and large patchy shadows in the lungs are the main clinical features of children with SMPP,which may be independent risk factors for predicting SMPP.

Objective:To investigate the long-term efficacy, safety and prognostic factors of intraoperative radiotherapy (IORT) for narrow-margin (resection margin < 1 cm) hepatectomy in patients with hepatocellular carcinoma (HCC) during radical surgery.Methods:A retrospective cohort study was conducted. The data of primary HCC patients undergoing radical surgery and narrow-margin hepatectomy IORT in the Cancer Hospital of the Chinese Academy of Medical Sciences from November 2009 to February 2019 were collected. IORT applied 6 MeV or 9 MeV electron beams and a single irradiation was given to the margin. Kaplan-Meier method was used for the overall survival (OS) and disease-free survival (DFS) analysis; log-rank test was used for survival comparison among subgroups. The recurrence patterns and adverse reactions were recorded. Univariate and multivariate Cox proportional hazards models were used to analyze the factors influencing the OS and DFS.Results:A total of 64 patients were enrolled, with the median age [ M ( Q1, Q3)] of 57 years (49, 63) years. All patients included 55 males (85.9%) and 9 females (14.1%). The median dose of IORT was 15 Gy (range: 12-17 Gy). The median follow-up time was 83.3 (64.4, 91.9) months. The 1-year, 3-year, 5-year, 7-year, 10-year OS rates were 90.4%, 80.6%, 75.5%, 71.4% and 47.6%, respectively; the 1-year, 3-year, 5-year, 7-year,10-year DFS rates were 77.8%, 68.1%, 59.6%, 57.6% and 38.4%, respectively. Univariate Cox regression analysis indicated that preoperative serum alpha-fetoprotein (AFP) > 400 ng/ml was an independent risk factor for poor OS (> 400 ng/ml vs. ≤ 400 ng/ml: HR = 6.57, 95% CI: 2.16-19.96, P < 0.001), while not the independent influencing factor of poor DFS ( HR = 1.71, 95% CI: 0.65-4.52, P = 0.277). The age ≤ 60 years or not, gender, viral hepatitis or not, American Joint Committee on Cancer stage, tumor diameter (> 5 cm or not), tumor number, degree of tumor differentiation, microvascular invasion or not, microsatellite nodules or not, anatomical liver resection or not, and the dose of IORT ≤15 Gy or not were not the independent influencing factors of poor OS and DFS (all P > 0.05). Kaplan-Meier method analysis showed that patients with preoperative serum AFP ≤ 400 ng/ml (48 cases) had better OS compared with those with preoperative serum AFP>400 ng/ml (16 cases) (5-year OS rate: 84.8% vs. 44.9%; 7-year OS rate: 79.9% vs.37.4%), and the difference was statistically significant ( P = 0.002). There was no statistically significant difference in the DFS between the 2 groups ( P = 0.134). During the follow-up, 28 patients (43.8%) relapsed, including 17 cases (26.6%) of early recurrence and 11 cases (17.2%) of late recurrence. No marginal recurrence was observed. There were 22 cases (34.4%) of intrahepatic recurrence alone, 2 cases (3.1%) of extrahepatic recurrence and 4 cases (6.3%) of stimutaneous recurrence inside and outside the liver. The 1-, 3-, 5- and 7-year cumulative recurrence rates inside the liver were 19.0%, 27.2%, 37.4% and 39.3% respectively, and the cumulative recurrence rates outside the liver were 6.4%, 8.0%, 9.6% and 9.6% respectively. There were no adverse reactions above grade 3 in the entire group. There were no surgery-related deaths within 30 d after the operation, and no radiation-induced liver disease occurred. Conclusions:Narrow-margin IORT helps HCC patients receiving hepatectomy to achieve favorable long-term survival and adverse reactions are tolerable. It can be used as a safe and effective adjuvant therapy alternative.

Computational analysis can accurately detect drug-gene interactions (DGIs) cost-effectively. However, transductive learning models are the hotspot to reveal the promising performance for unknown DGIs (both drugs and genes are present in the training model), without special attention to the unseen DGIs (both drugs and genes are absent in the training model). In view of this, this study, for the first time, proposed an inductive learning-based model for the precise identification of unseen DGIs. In our study, by integrating disease nodes to avoid data sparsity, a multi-relational drug-disease-gene (DDG) graph was constructed to achieve effective fusion of data on DDG intro-relationships and inter-actions. Following the extraction of graph features by utilizing graph embedding algorithms, our next step was the retrieval of the attributes of individual gene and drug nodes. In this way, a hybrid feature characterization was represented by integrating graph features and node attributes. Machine learning (ML) models were built, enabling the fulfillment of transductive predictions of unknown DGIs. To realize inductive learning, this study generated an innovative idea of transforming known node vectors derived from the DDG graph into representations of unseen nodes using node similarities as weights, enabling inductive predictions for the unseen DGIs. Consequently, the final model was superior to existing models, with significant improvement in predicting both external unknown and unseen DGIs. The practical feasibility of our model was further confirmed through case study and molecular docking. In summary, this study establishes an efficient data-driven approach through the proposed modeling, suggesting its value as a promising tool for accelerating drug discovery and repurposing.