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.

Gastric polyps, as a common digestive system disease, have shown an increasing detection rate and are regarded as one of the precancerous states of gastric cancer. In TCM, gastric polyps can be classified as diseases such as "stomachache" and "fullness and distension in the stomach". TCM holds that the disease is often related to the accumulation of pathogenic factors such as phlegm and blood stasis in the body to form "kenang", which has the characteristics of insidiousness, stubbornness, and recurrence. Deficiency of healthy qi and disorder of qi movement can lead to the adhesion of phlegm and blood stasis, which highly aligns with the etiology and pathogenesis of gastric polyps. The treatment principles are promoting blood circulation to remove blood stasis, regulating qi movement, and strengthening the body resistance to consolidate the essence. Understanding the etiology, pathogenesis, and treatment principles of gastric polyps from the theory of "kenang" has important guiding significance for clinical diagnosis and treatment, providing new ideas and methods for the treatment of gastric polyps.

[Objective] To establish a method for detecting the potency of recombinant human coagulation factor Ⅶa for injection. [Methods] By adding the sample and factor Ⅶ deficient plasma to the sample cup and activating the reaction with prothrombin time assay reagent (PT reagent), the coagulation time of the sample was determined by the change in magnetic bead swing amplitude in the sample cup. The logarithm of coagulation time was inversely proportional to the logarithm of human factor Ⅶa potency. [Results] Under the experimental conditions, the specificity of the methodology was evaluated through spiked recovery, and the recovery rates ranged from 90.0% to 110.0%. Within the range from 0.125 to 1.000 IU/mL, there was a good linear response between the potency and coagulation time of the standard and sample, with correlation coefficients r>0.99. As for the accuracy and repeatability, the recovery rates of various concentrations detected in the stock solution were 101.0%, 100.0% and 112.0%, respectively, with RSD values of 2.6%, 4.0% and 0.0%, respectively. The recovery rates of various concentrations in finished product testing were 104.0%, 94.7% and 112.0%, respectively, with RSD values of 1.9%, 2.4% and 0.0%, respectively. As for the intermediate precision, the RSD were 4.5% and 3.7%, respectively. After treated with sample diluent, the sample was tested at room temperature for 6 hours and still exhibited relatively stable biological activity. [Conclusion] This detection method is accurate, stable, easy to operate and highly automated, and is suitable for detecting the potency of recombinant human coagulation factor Ⅶa for Injection.

Objective To investigate the clinical manifestations of traditional Chinese medicine(TCM)and their associations with TCM constitutions in individuals who have migrated to plateau areas,and to provide a scientific basis for plateau health management.Methods Migrants living in areas above 3000 m were selected as research subjects.Data were collected by using TCM symptom assessment scales and constitution assessment scales.Descriptive statistical analysis was conducted to determine the incidence and severity of symptoms among individuals with different migration durations,and core symptoms were identified.Factor analysis was performed by using SPSS software to extract symptom clusters and explore the correlation between core symptoms and TCM constitutions.Results Among individuals who migrated to plateau areas,the incidence of discomfort symptoms was 83.44％.The five most common symptoms were dry skin(67.94％),forgetfulness(56.03％),dry mouth(52.06％),yellow urine(48.73％),and insomnia(47.14％).In the top 10 symptoms with the highest increase in incidence,yellow urine(33.51％)and forgetfulness(26.33％)were both present in the top 10 symptoms across different migration durations.Factor analysis extracted 5,2,4,and 6 symptom clusters from the overall population,individuals who migrated within 1 year,those who migrated for 1-2 years,and those who migrated over 2 years,respectively.Qi-deficiency constitution(QDC),blood stasis constitution(BSC),qi stagnation constitution(QSC),phlegm-dampness constitution(PDC),and dampness-heat constitution(DHC)were significantly positively correlated with forgetfulness.Conclusion Migrating to plateau areas can induce discomfort symptoms,and both the number and incidence of symptoms increase with longer migration durations.The number and incidence of high-frequency symptoms(incidence≥30％)increase with prolonged migration time.There are differences in the composition and severity of symptom clusters across different migration durations.QDC,BSC,QSC,PDC,and DHC are closely related to forgetfulness and can be considered risk constitutions for forgetfulness.Timely attention to changes in symptom clusters and constitutions can help prevent and mitigate the occurrence and development of symptoms.

OBJECTIVE To construct ensemble learning models for predicting high-use days of budesonide based on meteorological factors， thereby providing reference for hospital pharmacy management. METHODS Meteorological data for 2024 and outpatient budesonide usage data from the jurisdiction of Sanming Hospital of Integrated Traditional Chinese and Western Medicine were collected. High-use days were defined as the 75th percentile of outpatient budesonide usage， and a corresponding dataset was established. The prediction task was formulated as a classification problem， and three ensemble learning models were developed： Random Forest， Extreme Gradient Boosting （XGBoost）， and Histogram-based Gradient Boosting Classifier. Model performance was evaluated using accuracy， precision， recall， F1-score， and log-loss. Model interpretability was analyzed using Shapley Additive Explanations （SHAP）. RESULTS The Histogram-based Gradient Boosting Classifier achieved the best performance （accuracy＝0.75， F1-score＝0.48）， followed by XGBoost （accuracy＝0.74， F1-score＝0.43） and Random Forest （accuracy＝0.72， F1-score＝0.22）. SHAP results suggested that the prediction results of the last two models have the highest correction. CONCLUSIONS Ensemble learning models can effectively predict high-use days of budesonide， with the Histogram- based Gradient Boosting Classifier demonstrating the best predictive performance. Low temperature， high humidity， and low atmospheric pressure show significant positive impacts on the prediction of daily budesonide usage.

Objective A Social Care Needs Assessment Tool for Terminal Patients at Home is constructed and tested for its reliability and validity.Methods In view of the Social Ecosystem Theoiy,based on the semi-structured interviews,participatory observation and literature analysis of the social care needs of terminal patients at home,a questionnaire item pool was formed.Through 3 rounds of Delphi expert consultations,the initial version of the tool was formed.From April to December 2023,a convenient sampling method was used to select 504 terminal patients from 22 hospitals in 5 provinces as the research subjects.The reliability and validity of the tool were tested.Result The constructed tool in this study contained 3 dimensions:micro,meso,macro,with a total of 34 items.Cronbach's α of the tool was 0.966 and split-half reliability was 0.877;I-CVI at the item level was 0.875～1.000 and S-CVI/Ave was 0.989;the exploratory factor analysis results showed that the factors load of each dimension were greater than 0.4;the results of confirmatory factor analysis showed that the tool had good fitting degree.Conclusion The reliability and validity of the nursing-based social care needs assessment tool for terminal patients at home constructed in this study are good,and it can provide a valid tool for healthcare professionals to assess the home-based social care needs of terminal patients.

Asthma is a chronic inflammatory disease involving multiple inflammatory cells and cytokines. Its pathogenesis is complex, involving various cells and cytokines. Traditional Chinese medicine(TCM) theory suggests that the pathogenesis of asthma is closely related to the dysfunction of internal organs such as the lungs, spleen, and kidneys. In contrast, modern immunological studies have revealed the central role of T helper 1(Th1)/T helper 2(Th2) and T helper 17(Th17)/regulatory T(Treg) cellular immune imbalance in the pathogenesis of asthma. Th1/Th2 imbalance is manifested as hyperfunction of Th2 cells, which promotes the synthesis of immunoglobulin E(IgE) and the activation of eosinophil granulocytes, leading to airway hyperresponsiveness and inflammation.Meanwhile, Th17/Treg imbalance exacerbates the inflammatory response in the airways, further contributing to asthma pathology.Currently, therapeutic strategies for asthma are actively exploring potential targets for regulating the balance of Th1/Th2 and Th17/Treg immune responses. These targets include cytokines, transcription factors, key proteins, and non-coding RNAs. Precisely regulating the expression and function of these targets can effectively modulate the activation and differentiation of immune cells. In recent years,traditional Chinese medicine active ingredients have shown unique potential and prospects in the field of asthma treatment. Based on this, the present study systematically summarizes the efficacy and specific mechanisms of TCM active ingredients in treating asthma by regulating Th1/Th2 and Th17/Treg immune balance through literature review and analysis. These active ingredients, including flavonoids, terpenoids, polysaccharides, alkaloids, and phenolic acids, exert their effects through various mechanisms, such as inhibiting the activation of inflammatory cells, reducing the release of cytokines, and promoting the normal differentiation of immune cells. This study aims to provide a solid foundation for the widespread application and in-depth development of TCM in asthma treatment and to offer new ideas for clinical research and drug development of asthma.
Asthma/genetics* ; Humans ; Drugs, Chinese Herbal/chemistry* ; Th2 Cells/drug effects* ; Th17 Cells/drug effects* ; T-Lymphocytes, Regulatory/drug effects* ; Th1 Cells/drug effects* ; Animals ; Cytokines/immunology* ; Medicine, Chinese Traditional

Asthma, a chronic inflammatory airway disease with a high global prevalence, has a complex pathogenesis, in which airway remodeling plays a key role in the chronicity of the disease. Airway remodeling involves a series of pathophysiological changes, including airway epithelial damage, proliferation of mucous glands and goblet cells, subepithelial fibrosis, proliferation and migration of airway smooth muscle cells, and epithelial-mesenchymal transition. These complex pathological changes significantly increase airway resistance and responsiveness, forming an important pathological basis for refractory asthma. Currently, the regulatory mechanisms of airway remodeling focus on signaling pathways and regulatory targets. The signaling pathways include phosphatidylinositol 3-kinase(PI3K)/protein kinase B(Akt), nuclear factor-κB(NF-κB), transforming growth factor-β1(TGF-β1)/Smads, and mitogen-activated protein kinase(MAPK). The regulatory targets include microRNAs(miRNAs), competing endogenous RNAs(ceRNAs), long non-coding RNAs(lncRNAs), and circular RNAs(circRNAs). Key proteins involved in these processes include TGF-β1, silencing information regulator 2-related enzyme 1(SIRT1), chitinase 3-like protein 1(YKL-40), and adenosine deaminase-metalloproteinase 33(ADAM33). In recent years, the potential of traditional Chinese medicine in the treatment of asthma has become increasingly evident. Its active ingredients, extracts, and complexes can inhibit airway remodeling in asthma through multiple pathways, demonstrating a variety of effects, including anti-inflammatory actions, inhibition of smooth muscle cell proliferation and migration, regulation of epithelial-mesenchymal transition, attenuation of fibrosis and basement membrane thickening, reduction of mucus secretion, inhibition of vascular remodeling, modulation of immune imbalance, and antioxidative stress. This paper aims to provide an in-depth analysis of the pathogenesis and therapeutic targets of asthma, offering theoretical support and innovative strategies for clinical research and drug development in the treatment of asthma.
Asthma/pathology* ; Humans ; Airway Remodeling/drug effects* ; Drugs, Chinese Herbal/therapeutic use* ; Animals ; Signal Transduction/drug effects* ; Medicine, Chinese Traditional ; Transforming Growth Factor beta1/metabolism*

Objective To explore the incidence rate and independent risk factors of synchronous multiple early gastric cancer (SMEGC) in patients with early gastric cancer, and to provide evidence for early screening and intervention of high-risk population. Methods A retrospective analysis was performed on 308 patients with early gastric cancer who received treatment in the hospital from March 2019 to March 2024. The incidence rate of SMEGC was counted, and the risk factors were analyzed by univariate and multivariate Logistic regression analyses. Results Among the 308 patients with early gastric cancer in this study, 23 cases were SMEGC and 285 were single early gastric cancer, which were included in the SMEGC group and the single group respectively. The incidence rate of SMEGC was 7.47% (23/308). Compared with the single group, the proportions of male, smoking history, tumor diameter≤2 mm, chronic atrophic gastritis and intestinal metaplasia degree were higher in the SMEGC group (2=4.331、8.608、4.618、6.490、4.897，P=0.037、0.003、0.032、0.001、0.027). Logistic regression analysis suggested that chronic atrophic gastritis (OR=3.133, 95%CI: 1.240-7.918) and moderate-to-severe intestinal metaplasia (OR=3.171, 95%CI: 1.252-8.029) were independent risk factors for SMEGC (P<0.05). Conclusion Some patients with early gastric cancer are SMEGC. Chronic atrophic gastritis and moderate-to-severe intestinal metaplasia are independent risk factors affecting the occurrence of SMEGC. It is recommended to regularly screen high-risk patients and optimize management strategies to reduce the risk of SMEGC.

Objective:To investigate the characteristics of Internet addiction(IA)in adolescents with depression and explore its relationship with impulsivity and aggressive personality traits.Methods:A total of 71 adolescent patients with depressive disorders were recruited from the Child Psychiatry Outpatient Clinic of Peking University Sixth Hospital between April 2021 and November 2022 (15 males, 56 females; median age 14 [13, 15] years) as the depressive disorder group. Additionally, 83 healthy adolescents (27 males, 56 females; median age 14 [13, 17] years) were recruited as the control group during the same period. Internet addiction was assed using the Chinese version of Young′s Internet Addiction Test (YIAT), with a total score≥50 indicating internet addiction. Impulsivity was evaluated using the Barratt Impulsiveness Scale-11(BIS-11), and aggression was measured with the Buss-Perry Aggression Questionnaire(BPAQ). Differences in internet addiction, impulsivity, and aggression between the depression group and the control group were analyzed. Pearson correlation analysis was used to explore the correlation between internet addiction and impulsivity, aggression. Hierarchical linear regression models were used to analyze the factors influencing internet addiction, and a parallel mediation model was used to examine the mediating effect of impulsivity and aggressive personality traits in the relationship between depressive disorders and internet addiction.Results:The prevalence of IA was significantly higher in adolescents with depression than the healthy control group [57.75%(41/71) vs 31.33%(26/83); χ 2=10.87, P<0.001]. Adolescents with depressive disorders also exhibited higher impulsivity (65.5±9.2 vs 57.0±9.2, t=-5.72, P<0.001) and aggression (56.3±16.0 vs 42.4±15.1, t=-5.13, P<0.001) compared to the control group. Internet addiction was positively correlated with aggression ( r=0.47, P<0.01) and impulsivity ( r=0.57, P<0.01). Hierarchical regression analysis with the YIAT total score as the dependent variable revealed that impulsivity ( β=0.48, P<0.001) and aggression ( β=0.24, P<0.001) significantly predicted internet addiction. Mediation analysis indicated that depressive disorders indirectly indirectly influenced internet addiction through parallel paths of impulsivity and aggression, with a total indirect effect of 0.543 (95% CI: 0.362-0.761). Conversely, internect addiction influenced depressive disorders through reverse parallel pathway of impulsivity and aggression with a total indirect effect of 0.038 (95% CI: 0.021-0.067). Direct effects were not significant in either direction. Conclusion:Adolescents with depressive disorders exhibit more internet addiction. Impulsivity and aggressive personality traits play bidirectional mediating roles in the relationship between depressive disorders and internet addiction.