ObjectiveTo investigate the current status of ethical sensitivity among clinical nursing interns in the context of artificial intelligence （AI） and analyze its influencing factors. MethodsAdopting mixed research methods and convenience sampling， a total of 237 nursing interns from a tertiary A hospital in Xi’an were selected as research subjects. Data were collected using a general information questionnaire and the Nursing Students’ Ethical Sensitivity Scale， and semi-structured interviews were conducted with 8 nursing interns. ResultsThe total score of ethical sensitivity among nursing interns was （33.98±6.32）， which was at a moderate level. Multiple linear regression analysis revealed that academic degree （undergraduate： β=0.147， P<0.05； postgraduate： β=0.139， P<0.05）， affinity for the nursing profession （β=0.118， P<0.05）， whether they had taken nursing ethics courses （β=-0.124， P<0.05）， and familiarity with artificial intelligence （β=-0.159，P<0.05） were influencing factors of ethical sensitivity among nursing interns. Four themes were extracted from semi-structured interviews， namely， the incomplete mastery of nursing ethics-related knowledge among nursing interns， weakened ethical sensitivity in the AI teaching scenario of nursing interns， insufficient professional identity affecting the development of nursing interns’ ethical sensitivity， and technological dependence leading to the lack of humanistic care among nursing interns. ConclusionEthical sensitivity of nursing interns represents a moderate level， primarily influenced by educational background， degree of fondness for the nursing profession， learning experience of nursing ethics courses， and familiarity with AI. Nursing educators and clinical administrators urgently need to establish a sustainable school-hospital collaborative model of nursing ethics education， attach importance to the cultivation of ethical awareness and value guidance for nursing interns， and strengthen the intensity and depth of nursing ethics education among nursing interns， thereby improving their level of ethical sensitivity in the context of AI.

Objective To explore the prognosis-related genes of lung adenocarcinoma(LUAD)and establish a prognostic prediction model for LUAD.Methods The differentially expressed genes of LUAD tissues and adjacent normal tissues in the GSE43458,GSE7670,and GSE140797 datasets were screened.The protein-protein interaction(PPI)network analysis,gene ontology(GO)function,Kyoto Encyclopedia of Genes and Genomes(KEGG)signaling pathway enrichment analyses,least absolute shrinkage and selection operator for prognosis coefficient screening,disease-specific survival analysis,Cox regression analysis,and gene correlation analysis were performed.Independent prognostic genes of LUAD were screened from the differential genes,and a prognostic prediction model of LUAD was established.The expression of independent prognostic genes was analyzed,and the predictive model was evaluated by receiver operating characteristic(ROC)curve.The GSE68465 data set was used as an external validation set to verify the predictive model.Results There were 197 up-regulated differential genes and 77 down-regulated differential genes in LUAD and adjacent normal tissues common to the three datasets.Through stepwise screening,two genes,IL7R and SLC2A1,were identified as independent prognostic factors for LUAD.IL7R was an independent protective factor,while the SLC2A1 was an independent risk factor.A prediction model for curve was built with IL7R and SLC2A1.The prediction model for LUAD constructed with IL7R and SLC2A1 is as follows:Risk score=(-0.694)×expression level of IL7R+0.763×expression level of SLC2A1.Conclusion This study screened out IL7R as an independent prognostic protective factor for LUDA,and SLC2A1 as an independent prognostic risk factor for LUAD.The LUDA prediction model constructed based on these two genes has good predictive ability and generalization ability,which can provide references for the research and clinical individualized treatment of LUAD.

Objective To explore a deep learning-based automatic bone age estimation model for elbow joint X-ray images of Chinese Han adolescents and children and evaluate its performance.Methods A total of 943(517 males and 426 females)elbow joint frontal view X-ray images of Chinese Han ado-lescents and children aged 6.00 to<16.00 years were collected from East,South,Central and North-west China.Three experimental schemes were adopted for bone age estimation.Scheme 1:Directly in-put preprocessed images into the regression model;Scheme 2:Train a segmentation network using"key elbow joint bone annotations"as labels,then input segmented images into the regression model;Scheme 3:Train a segmentation network using"full elbow joint bone annotations"as labels,then in-put segmented images into the regression model.For segmentation,the optimal model was selected from U-Net,UNet++and TransUNet.For regression,VGG16,VGG19,InceptionV2,InceptionV3,ResNet34,ResNet50,ResNet101 and DenseNet121 models were selected for bone age estimation.The dataset was randomly split into 80%(754 samples)for training and validation for model fitting and hyperparameter tuning,and 20%(189 samples)as an internal test set to test the performance of the trained model.An additional 104 elbow joint X-ray images from the same demographic and age group were col-lected and used as an external test set.Model performance was evaluated by comparing the mean ab-solute error(MAE),root mean square error(RMSE),accuracies within±0.7 years(P±0.7 years)and±1.0 years(P±1.0 years)between the estimated age and the actual age,and by drawing radar charts,scat-ter plots,and heatmaps.Results When segmented with Scheme 3,the UNet++model achieved good segmentation performance with a segmentation loss of 0.000 4 and an accuracy of 93.8%at a learning rate of 0.000 1.In the internal test set,the DenseNet121 model with Scheme 3 yielded the best results with MAE,P±0.7 years and P±1.0 years being 0.83 years,70.03%,and 84.30%,respectively.In the external test set,the DenseNet121 model with Scheme 3 also performed best,with an average MAE of 0.89 years and an average RMSE of 1.00 years.Conclusion When performing automatic bone age estima-tion using elbow joint X-ray images in Chinese Han adolescents and children,it is recommended to use the UNet++model for segmentation.The DenseNet121 model with Scheme 3 achieves optimal per-formance.Using segmentation networks,especially that trained with annotation areas encompassing the full elbow joint including the distal humerus,proximal radius,and proximal ulna,can improve the ac-curacy of bone age estimation based on elbow joint X-ray images.

Objective To explore a deep learning network model suitable for bone age estimation using shoulder joint X-ray images in Chinese Han adolescents.Methods A retrospective collection of 1 286 shoulder joint X-ray images of Chinese Han adolescents aged 12.0 to<18.0 years(708 males and 578 females)was conducted.Using random sampling,approximately 80%of the samples(1 032 cases)were selected as the training and validation sets for model learning,selection and optimization,and the other 20%samples(254 cases)were used as the test set to evaluate the model's generalization ability.The original single-channel shoulder joint X-ray images and dual-channel inputs combining original images with segmentation labels(manually annotated shoulder joint regions multiplied pixel-by-pixel with original images,followed by segmentation via the U-Net++network to retain only key shoulder joint region information)were respectively input into four network models,namely VGG16,ResNet18,ResNet50 and DenseNet121 for bone age estimation.Additionally,manual bone age estimation was con-ducted on the test set data,and the results were compared with the four network models.The mean absolute error(MAE),root mean square error(RMSE),coefficient of determination(R2),and Pear-son correlation coefficient(PCC)were used as main evaluation indicators.Results In the test set,the bone age estimation results of the four models with dual-channel input of shoulder joint X-ray images outperformed those with single-channel input in all four evaluation indicators.Among them,DenseNet121 with dual-channel input achieved best results with MAE of 0.54 years,RMSE of 0.82 years,R2 of 0.76,and PCC(r)of 0.88.Manual estimation yielded an MAE of 0.82 years,ranking second only to dual-channel DenseNet121.Conclusion The DenseNet121 model with dual-channel input combined with original images and segmentation labels is superior to manual evaluation results,and can effectively estimate the bone age of Chinese Han adolescents.

Objective To investigate the relationship between the levels of type Ⅲ procollagen(PCⅢ)and heme-binding protein(HPX)in peripheral blood,blood lipid and liver fibrosis in patients with nonalcoholic steatohepatitis(NASH).Methods Totally 126 patients with NASH admitted to the hospital from January 2021 to December 2023 were selected as NASH group,and they were divided into 3 subgroups according to the degree of liver fibrosis:no liver fibrosis group(22 cases),mild group(63 cases),moderate and severe group(41 cases).In addition,150 healthy subjects in the same period were selected as the control group.Enzyme-linked immunosorbent assay(ELISA)was used to detect and compare the levels of PC Ⅲ and HPX in periph-eral blood of all groups,and Pearson correlation analysis was used to explore the correlation between peripher-al blood PC Ⅲ and HPX levels and related indexes of blood lipids in NASH patients.The predictive value of peripheral blood PC Ⅲ and HPX for liver fibrosis in NASH patients was evaluated by receiver operating char-acteristic(ROC)curve.Results The levels of PC Ⅲ and HPX,as well as total cholesterol(TC),triglyceride(TG)and low density lipoprotein cholesterol(LDL-C)in NASH group were higher than those in control group,and the levels of high density lipoprotein cholesterol(HDL-C)were lower than those in control group,and the differences were statistically significant(P＜0.05).Pearson correlation analysis showed that the lev-els of PCⅢ and HPX in peripheral blood of NASH patients were positively correlated with TC,TG and LDL-C(P＜0.05),while negatively correlated with HDL-C(P＜0.05).The levels of PC Ⅲ and HPX in peripheral blood of the non-fibrosis group were lower than those of the mild and moderate severe groups,and the mild group was lower than that of the moderate and severe group,and the differences were statistically significant(P＜0.05).The area under the curve(AUC)of peripheral blood PC Ⅲ and HPX in predicting liver fibrosis in NASH patients were 0.757 and 0.861,respectively,and the cut-off values were 135.51 ng/mL and 804.86 mg/L,respectively.The AUC of the combined prediction for liver fibrosis was 0.905,which was higher than that predicted by the two alone.Conclusion The level of PC Ⅲ and HPX in peripheral blood is closely related to the level of blood lipids and the degree of liver fibrosis in NASH patients,which can be used as potential bi-omarkers to predict liver fibrosis in NASH patients.

Objective: To investigate the nutritional status and influencing factors among Tibetan and Mongolian children and adolescents aged 7-18 years in high-altitude regions, so as to provide evidence for early prevention and control of malnutrition in this population. Methods: From May to June 2022, a cluster sampling method was employed to recruit 1 019 Tibetan and Mongolian children and adolescents aged 7-18 years from two primary and secondary schools in Golmud City. Physical examinations, dietary frequency questionnaires, and physical activity assessments were conducted. Nutritional status was classified as obesity, combined overweight/obesity, underweight, or central obesity according to national standards including Screening for Overweight and Obesity among School-age Children and Adolescents, Screening Standard for Malnutrition of School-age Children and Adolescents, Blue Book on Obesity Prevention and Control in China. Chi-square tests, t-test and Logistic regression analyses were performed to identify factors associated with different nutritional statuses. Results: The detection rates of obesity, combined overweight/obesity, underweight, and central obesity were 8.0%, 18.1%, 5.2%, and 19.7%, respectively. The height of children and adolescents across all age groups was generally lower than the national standard values. Tibetan participants exhibited significantly lower height-for-age Z-scores (HAZ)(9-10, 13-17 years, Z =2.01, 2.78, 4.16, 3.38, 4.12, 3.63, 3.00) and BMI-for-age Z-scores (BAZ) compared to Mongolian participants ( Z =-2.95, -2.47, -2.31, -2.89, -2.14, -2.17)( P < 0.05 ). Multivariate Logistic regression revealed that Mongolian children and adolescents had higher risks of obesity ( OR =2.20) and combined overweight/obesity ( OR = 2.18 ) ( P <0.05). Additionally, insufficient moderate-to-vigorous physical activity (MVPA) was associated with an increased risk of central obesity ( OR =1.48, P <0.05), compared with children and adolescents who meet the standard of MVPA. Conclusions The rates of overweight and obesity among Tibetan and Mongolian children and adolescents in Golmud City are higher, influenced by multiple factors. Nutrition interventions and physical activity strategies tailored to ethnic characteristics should be implemented, with emphasis on promoting MVPA to improve nutritional outcomes in this population.

OBJECTIVE: Baicalein has been reported to have wide therapeutic effects that act through its anti-inflammatory activity. This study examines the effect and mechanism of baicalein on sepsis-induced cardiomyopathy (SIC). METHODS: A thorough screening of a small library of natural products, comprising 100 diverse compounds, was conducted to identify the most effective drug against lipopolysaccharide (LPS)-treated H9C2 cardiomyocytes. The core target proteins and their associated signaling pathways involved in baicalein's efficacy against LPS-induced myocardial injury were predicted by network pharmacology. RESULTS: Baicalein was identified as the most potent protective agent in LPS-exposed H9C2 cardiomyocytes. It exhibited a dose-dependent inhibitory effect on cell injury and inflammation. In the LPS-induced septic mouse model, baicalein demonstrated a significant capacity to mitigate LPS-triggered myocardial deficits, inflammatory responses, and ferroptosis. Network pharmacological analysis and experimental confirmation suggested that hypoxia-inducible factor 1 subunit α (HIF1-α) is likely to be the crucial factor in mediating the impact of baicalein against LPS-induced myocardial ferroptosis and injury. By combining microRNA (miRNA) screening in LPS-treated myocardium with miRNA prediction targeting HIF1-α, we found that miR-299b-5p may serve as a regulator of HIF1-α. The reduction in miR-299b-5p levels in LPS-treated myocardium, compared to the control group, was reversed by baicalein treatment. The reverse transcription quantitative polymerase chain reaction, Western blotting, and dual-luciferase reporter gene analyses together identified HIF1-α as the target of miR-299b-5p in cardiomyocytes. CONCLUSION Baicalein mitigates SIC at the miRNA level, suggesting the therapeutic potential of it in treating SIC through the regulation of miR-299b-5p/HIF1-α/ferroptosis pathway. Please cite this article as: Zhou WY, Du JK, Liu HH, Deng L, Ma K, Xiao J, Zhang S, Wang CN. Baicalein attenuates lipopolysaccharide-induced myocardial injury by inhibiting ferroptosis via miR-299b-5p/HIF1-α pathway. J Integr Med. 2025; 23(5):560-575.
Flavanones/pharmacology* ; Animals ; MicroRNAs/genetics* ; Lipopolysaccharides ; Hypoxia-Inducible Factor 1, alpha Subunit/genetics* ; Ferroptosis/drug effects* ; Mice ; Myocytes, Cardiac/metabolism* ; Signal Transduction/drug effects* ; Rats ; Male ; Mice, Inbred C57BL ; Cardiomyopathies/etiology* ; Cell Line ; Sepsis/complications*

OBJECTIVE: Exposure to polycyclic aromatic hydrocarbons (PAHs) or metal(loid)s individually has been associated with neural tube defects (NTDs). However, the impacts of PAH and metal(loid) co-exposure and potential interaction effects on NTD risk remain unclear. We conducted a case-control study in China among population with a high prevalence of NTDs to investigate the combined effects of PAH and metal(loid) exposures on the risk of NTD. METHODS: Cases included 80 women who gave birth to offspring with NTDs, whereas controls were 50 women who delivered infants with no congenital malformations. We analyzed the levels of placental PAHs using gas chromatography and mass spectrometry, PAH-DNA adducts with ³²P-post-labeling method, and metal(loid)s with an inductively coupled plasma mass spectrometer. Unconditional logistic regression was employed to estimate the associations between individual exposures and NTDs. Least absolute shrinkage and selection operator (LASSO) penalized regression models were used to select a subset of exposures, while additive interaction models were used to identify interaction effects. RESULTS: In the single-exposure models, we found that eight PAHs, PAH-DNA adducts, and 28 metal(loid)s were associated with NTDs. Pyrene, selenium, molybdenum, cadmium, uranium, and rubidium were selected through LASSO regression and were statistically associated with NTDs in the multiple-exposure models. Women with high levels of pyrene and molybdenum or pyrene and selenium exhibited significantly increased risk of having offspring with NTDs, indicating that these combinations may have synergistic effects on the risk of NTDs. CONCLUSION Our findings suggest that individual PAHs and metal(loid)s, as well as their interactions, may be associated with the risk of NTDs, which warrants further investigation.
Humans ; Neural Tube Defects/chemically induced* ; Polycyclic Aromatic Hydrocarbons/adverse effects* ; Female ; Case-Control Studies ; China/epidemiology* ; Adult ; Pregnancy ; Environmental Pollutants ; Maternal Exposure/adverse effects* ; Metals/toxicity* ; Young Adult ; Risk Factors

OBJECTIVE: Hepatocellular carcinoma (HCC) is sensitive to ferroptosis, a new form of programmed cell death that occurs in most tumor types. However, the mechanism through which ferroptosis modulates HCC remains unclear. This study aimed to investigate the oncogenic role and prognostic value of FANCD2 and provide novel insights into the prognostic assessment and prediction of immunotherapy. METHODS: Using clinicopathological parameters and bioinformatic techniques, we comprehensively examined the expression of FANCD2 macroscopically and microcosmically. We conducted univariate and multivariate Cox regression analyses to identify the prognostic value of FANCD2 in HCC and elucidated the detailed molecular mechanisms underlying the involvement of FANCD2 in oncogenesis by promoting iron-related death. RESULTS: FANCD2 was significantly upregulated in digestive system cancers with abundant immune infiltration. As an independent risk factor for HCC, a high FANCD2 expression level was associated with poor clinical outcomes and response to immune checkpoint blockade. Gene set enrichment analysis revealed that FANCD2 was mainly involved in the cell cycle and CYP450 metabolism. CONCLUSION To the best of our knowledge, this is the first study to comprehensively elucidate the oncogenic role of FANCD2. FANCD2 has a tumor-promoting aspect in the digestive system and acts as an independent risk factor in HCC; hence, it has recognized value for predicting tumor aggressiveness and prognosis and may be a potential biomarker for poor responsiveness to immunotherapy.
Humans ; Carcinoma, Hepatocellular/diagnosis* ; Liver Neoplasms/diagnosis* ; Immunotherapy ; Fanconi Anemia Complementation Group D2 Protein/metabolism* ; Prognosis ; Male ; Female ; Middle Aged ; Biomarkers, Tumor/metabolism*