Objective:To establish a framework of entrustable professional activity indicators for non-anesthesiology residents during rotation in the Department of Anesthesiology, standardize the training process, and provide an effective evaluation method.Methods:Based on literature review and discussions, a preliminary expert consultation questionnaire was developed. From July to November 2024, a modified Delphi method was adopted and relevant experts were invited to assess the importance, validity, and feasibility of each indicator using a 5-point Likert scale. The results were used to screen and refine the entrustable professional activity indicators for non-anesthesiology residents during rotation in the Department of Anesthesiology.Results:In the two rounds of expert consultation, the valid questionnaire return rate reached 100.00%, with an expert judgment basis coefficient of 0.73 and a familiarity coefficient of 0.90. Based on expert feedback, the final framework retained 3 first-level indicators and 12 second-level indicators. Modifications included renaming "Anesthesia Management" to "Anesthetic Drug Management", swapping the order of "Intraoperative Emergency Management" and "Airway Management", and removing the indicator "Resuscitation Assessment".Conclusions:This study preliminarily developed a framework of entrustable professional activity indicators for non-anesthesiology residents during rotation in the Department of Anesthesiology. The framework provides a simple and practical competency evaluation method for standardized training, which can enhance training quality and effectiveness.

Skeletal muscle dysfunction is a common extra-pulmonary complication in patients with chronic ob-structive pulmonary disease(COPD),significantly impacting exercise capacity and quality of life,leading to a poorer prognosis and increased mortality.Oxidative stress closely associates with the development and progression of skeletal muscle dysfunction in COPD.Exercise,a core component of pulmonary rehabilitation,stands as the primary non-pharma-cological treatment for skeletal muscle dysfunction in COPD patients and exerts a positive modulating effect on oxidative stress.This paper reviews the effects of oxidative stress on skeletal muscle dysfunction in COPD and discusses the mecha-nisms by which exercise improves skeletal muscle dysfunction in COPD from an anti-oxidative stress perspective.It has been found that oxidative stress affects the structure and function of muscles in COPD patients by upregulating the protein hydrolysis system,disrupting mitochondrial function,and impairing calcium homeostasis.Mechanisms by which exercise modulates oxidative stress to improve skeletal muscle dysfunction include the activation of antioxidant genes such as silent mating type information regulation 2 homolog 1 and nuclear factor erythroid 2 related factor to enhance the body's antioxi-dant capacity,inhibiting muscle atrophy.Exercise also regulates mitochondrial reactive oxygen species metabolism,im-proving mitochondrial function,and reduces oxidase activity to protect sarcoplasmic reticulum calcium regulation.In con-clusion,the regulation of skeletal muscle oxidative stress by exercise is a crucial target for improving skeletal muscle dys-function in COPD.

Purpose To investigate the value of intratumoral and different ranges of peritumoral radiomics features of the primary lesion of breast cancer based on ultrasound images in predicting axillary lymph node metastasis(ALNM),and to explore the best peritumoral range.Materials and Methods A total of 312 cases confirmed by pathology in breast cancer patients with preoperative ultrasound images from June 2022 to February 2024 in Binzhou Medical University Hospital were retrospectively enrolled,and were randomly divided into training set and testing set according to the 7∶3 proportion.The tumor border of the ultrasound images was manually delineated as the intratumoral region of interest,and the peritumoral region of interest was obtained by conformal automatically extended different range(1,2,3,4 and 5 mm).The radiomics features were screened.Based on the selected optimal radiomics features,random forest classifier was used to construct three types of radiomics models(intratumoral model,5 peritumoral models,and 5 intratumoral+peritumoral models).The performance and clinical practicability of the models was assessed the area under the curve(AUC)and decision curve analysis.Results The AUCs of the intratumoral+peritumoral radiomics models for predicting ALNM in the training set and test set were 0.807-0.873,0.728-0.780,respectively,which were superior to those of the single intratumoral radiomics models(0.822,0.758)and peritumoral radiomics models(0.722-0.768,0.650-0.710).The intratumoral+peritumoral 3 mm radiomics model showed the best predictive performance,with AUC of 0.873 in the training set and 0.780 in the test set,respectively,and the decision curve showed that the model had a good clinical net benefit.Conclusion The combined intratumoral and peritumoral radiomics features of the primary lesion of breast cancer based on ultrasound images can effectively predict ALNM,and 3 mm peritumoral may be the best peritumoral range for predicting ALNM.

Objective:To explore the dynamic change trajectory and influencing factors of postoperative fatigue (POF) in patients with early digestive tract cancer undergoing endoscopic submucosal dissection (ESD), so as to provide theoretical basis for individualized management of such patients.Methods:Using cross-sectional survey and convenient sampling method, the patients who underwent ESD for early cancer of digestive tract in the endoscopic center of the Second Affiliated Hospital of Zhejiang University School of Medicine from January to June 2024 were selected as the research objects. The questionnaires were conducted at 30 min, 24 h, 3 days, 5 days, 7 days after ESD with Christensen's postoperative fatigue score. Spearman test was used to analyze the correlation between pain, insomnia and POF. The latent variable growth model was used to identify the potential categories of POF trajectory, and the influencing factors were analyzed by Logistic regression.Results:A total of 232 patients were finally induded, with ages of 19-94(59.53 ± 13.29) years, including 120 males and 112 femalss. The POF level of patients with early cancer of digestive tract showed a downward trend one week after operation. Three postoperative fatigue trajectories were fitted, 9.05% in moderate or severe fatigue low-speed smooth descent group (C1 group); 32.76% in moderate fatigue first decreased quickly and then slowly group (C2 group) and 58.19% in mild fatigue continuous decline group (C3 group). The result of Logistic regression analysis showed that, compared with C1 group, people without religious beliefs were morelikely to enter C2 group [ β = 1.572, OR = 4.818(1.033 - 22.465), P<0.05]; compared with C3 group, patients with high pain level and severe insomnia degree were likely to enter C1 [ β = 2.621, 0.663, OR were 13.754(2.692 - 70.283) and 1.942(1.429 - 2.638), both P<0.05] and C2 [ β = 2.010, 0.491, OR were 7.464(1.890 - 29.482) and 1.634(1.348 - 1.982), both P<0.05] group. Conclusions:There were three potential types of POF in patients with early digestive tract cancer ESD. Medical staff should pay attention to patients with severe insomnia, intense pain and religious beliefs, and give staged fatigue assessment and individualized intervention, so as to reduce the level of POF and promote rapid recovery.

Purpose To investigate the value of intratumoral and different ranges of peritumoral radiomics features of the primary lesion of breast cancer based on ultrasound images in predicting axillary lymph node metastasis(ALNM),and to explore the best peritumoral range.Materials and Methods A total of 312 cases confirmed by pathology in breast cancer patients with preoperative ultrasound images from June 2022 to February 2024 in Binzhou Medical University Hospital were retrospectively enrolled,and were randomly divided into training set and testing set according to the 7∶3 proportion.The tumor border of the ultrasound images was manually delineated as the intratumoral region of interest,and the peritumoral region of interest was obtained by conformal automatically extended different range(1,2,3,4 and 5 mm).The radiomics features were screened.Based on the selected optimal radiomics features,random forest classifier was used to construct three types of radiomics models(intratumoral model,5 peritumoral models,and 5 intratumoral+peritumoral models).The performance and clinical practicability of the models was assessed the area under the curve(AUC)and decision curve analysis.Results The AUCs of the intratumoral+peritumoral radiomics models for predicting ALNM in the training set and test set were 0.807-0.873,0.728-0.780,respectively,which were superior to those of the single intratumoral radiomics models(0.822,0.758)and peritumoral radiomics models(0.722-0.768,0.650-0.710).The intratumoral+peritumoral 3 mm radiomics model showed the best predictive performance,with AUC of 0.873 in the training set and 0.780 in the test set,respectively,and the decision curve showed that the model had a good clinical net benefit.Conclusion The combined intratumoral and peritumoral radiomics features of the primary lesion of breast cancer based on ultrasound images can effectively predict ALNM,and 3 mm peritumoral may be the best peritumoral range for predicting ALNM.

With the change of infectious disease incidence pattern and the development of related technologies, progresses have been made in the research of infectious disease epidemiology. In recent years, due to the change in the requirements of infectious disease prevention and control, the research focus has expanded from common infectious diseases to diseases which have been eliminated or might be eliminated, as well as emerging and re-emerging infectious diseases. Infectious disease data has been characterized by multiple sources and modalities. Along with the rapid development of pathogen detection methods, infectious disease surveillance has shifted from a single disease-targted one to a comprehensive one. Moreover, novel technologies such as multi-omics and artificial intelligence have been applied in infectious disease epidemiology research. The international cooperation in this field has become increasingly crucial, and the revision of the International Health Regulations and the negotiation of pandemic agreement will have a profound impact. In the future, infectious disease epidemiology research will develop with more powerful tools to improve its capabilities.

Objective : To explore the association between serum γ-aminobutyric acid ( GABA) levels and the risk of developing type 2 diabetes( T2DM) ． Methods : 187 cases of T2DM patients attending the hospital were selected as the T2DM group，and 187 cases of non-T2DM population attending the same period of time were selected as the control group according to age ( ± 3 years) and gender 1 ∶ 1．On-site questionnaires and physical examination were conducted for the study subjects，and serum levels of GABA，Malondialdehyde ( MDA) and activities of superoxide dismutase ( SOD) and Glutathione peroxidase ( GSH-Px) were detected by using ELISA kits．The differences in the levels of GABA and oxidative stress indicators ( SOD，GSH-Px，MDA) between the two groups were compared， and the correlation between GABA and oxidative stress indicators was analyzed by Spearman's method; GABA and oxidative stress indicators were divided into three groups according to their control quartiles，respectively ［low level group ( Q1: ＜P25) ，medium level group ( Q2: P25 －P75) ，high level group ( Q3: ＞P75) ］，and conditional logistic regression was applied to analyze the relationship between GABA，oxidative stress indicators and the risk of develo- ping T2DM; the dose-response relationship between GABA，oxidative stress indicators and the risk of developing T2DM was analyzed by using restricted cubic spline ( RCS) ． Results : T2DM group ( P＜0. 05) ．Spearman's correlation analysis showed that GABA level was positively correlated with SOD and GSH-Px activities and negatively correlated with MDA level ( P＜0. 001) ．Conditional logistic regression analysis showed that medium levels of SOD and GSH-Px as well as medium and high levels of GABA were protective factors for T2DM compared with low levels in each group ( P＜0. 05) ．RCS results showed that a negative dose-response relationship between GABA，GSH-Px and the risk of developing T2DM，and SOD showed a trend of decreasing and then increasing the risk of developing T2DM ( P＜0. 05) ． Conclusion Serum GABA levels have been associated with the risk of developing T2DM．As serum GABA levels increase，the risk of developing T2DM may decrease．

With the rapid advancement of artificial intelligence technology, chatbots have shown great potential in the healthcare sector. From personalized health advice to chronic disease management and psychological support, chatbots have demonstrated significant advantages in improving the efficiency and quality of healthcare services. As the scope of their applications expands, the relationship between technological complexity and practical application scenarios has become increasingly intertwined, necessitating a more comprehensive evaluation of both aspects. This paper, from the perspective of he althcare applications, systematically reviews the technological pathways and development of chatbots in the medical field, providing an in-depth analysis of their performance across various medical scenarios. It thoroughly examines the advantages and limitations of chatbots, aiming to offer theoretical support for future research and propose feasible recommendations for the broader adoption of chatbot technologies in healthcare.

Objective:To develop a post competence assessment scale for nurses in the health management (physical examination) center and assess its reliability and validity.Methods:This study adopted an empirical approach. A total of 801 nurses from the health management (physical examination) center were recruited to participate in this study. A research team was formed in August 2024. This team transformed the previously constructed core competence evaluation index system for health management specialist nurses in the health management (physical examination) center (comprising 6 first-level indicators and 70 third-level indicators) into a preliminary post competence assessment scale. Seven experts evaluated the content validity of the scale. In September 2024, a pilot survey was conducted among 27 nurses from the health management (physical examination) center of Sichuan Provincial People′s Hospital using convenience sampling. From October to November 2024, the first main survey was administered to 385 nurses of health management (physical examination) center across 54 cities in China using both convenience sampling and snowball sampling methods, followed by exploratory factor analysis (EFA). Subsequently, utilizing the refined scale obtained after eliminating certain items, a second main survey was conducted among 389 nurses in the health management (physical examination) center, followed by a confirmatory factor analysis (CFA). The reliability of the final scale was assessed using Cronbach′s α coefficient, split-half reliability, composite reliability, and test-retest reliability.Results:The finalized scale for nurses′ post competency in health management (physical examination) center comprises five dimensions—basic nursing service competency, health management practice competency, knowledge integration competency, professional development competency, and professional attitude—with a total of 57 items. The item level content validity index (I-CVI) of the items of the content validity display scale ranged from 0.857 to 1.000, and the content validity index of each dimension ranged from 0.984 to 1.000. The scale-level Content Validity index/average (S-CVI/Ave) was 0.995. The contribution rate of the 6 factors extracted by EFA was 74.07%. After group discussion and CFA, the scale of the 5-factor structural equation model was constructed. The total Cronbach′s α coefficient of the scale was 0.986, the split-half reliability was 0.865, the composite reliability was 0.960-0.980, the total table test-retest reliability was 0.762, and the test-retest reliability of each dimension was 0.681-0.731.Conclusion:The developed assessment scale for assessing the post competence of nurses in the health management (physical examination) center demonstrates excellent reliability and validity.

With the change of infectious disease incidence pattern and the development of related technologies, progresses have been made in the research of infectious disease epidemiology. In recent years, due to the change in the requirements of infectious disease prevention and control, the research focus has expanded from common infectious diseases to diseases which have been eliminated or might be eliminated, as well as emerging and re-emerging infectious diseases. Infectious disease data has been characterized by multiple sources and modalities. Along with the rapid development of pathogen detection methods, infectious disease surveillance has shifted from a single disease-targted one to a comprehensive one. Moreover, novel technologies such as multi-omics and artificial intelligence have been applied in infectious disease epidemiology research. The international cooperation in this field has become increasingly crucial, and the revision of the International Health Regulations and the negotiation of pandemic agreement will have a profound impact. In the future, infectious disease epidemiology research will develop with more powerful tools to improve its capabilities.