Medical ethics not only reflects the individual professional conduct of medical professionals， but also serves as the cornerstone for the operation of the healthcare system， directly linking to patients’ health rights and interests and overall social trust. The outbreak of public health emergencies has exerted a tremendous impact on people’s lives. During this period， clinicians in China have stood the test and demonstrated fearless dedication， which highlights the importance of medical ethics education. Clinicians possess dual identities as both medical professionals and patients. Their thoughts and perceptions evolve with the times， posing new challenges to medical ethics education of clinicians and carrying profound significance for improving the quality of medical services and safeguarding public health. This study adopted Strengths-Weaknesses-Opportunities-Threats （SWOT） theory to analyze and summarize the current situation， strengths， weaknesses， opportunities， and threats of medical ethics education， highlighting the urgent need to explore novel educational pathways. These will provide guidance for promoting the moral development of medical professionals and improving the quality of medical services， contribute to cultivating more physicians with dedication to serve society effectively， and drive the healthy development of China’s medical industry.

Objective To analyze the differences and connections between the current grading and classification methods for nuclear medicine workplaces, and to provide technical guidance for environmental impact assessments and technical reviews. Methods By comparing the objects, purposes, and computational approaches between the two methods, this article illustrates the usage of both methods through specific examples and analyzes the relationship between them. Results The two methods differed in objects, purposes, and computational approaches. The A, B, and C grading scheme was primarily used to establish the level of administrative supervision for an entire nuclear medicine workplace. In contrast, the I, II, and III classification system specifies the hardware facilities and engineering protection requirements of internal places or rooms. Conclusion These two methods are complementary and collectively provide a complete framework for the assessment of nuclear medicine workplaces.

Background and Aims:Gamma-aminobutyric acid(GABA),the principal inhibitory neurotransmitter in the central nervous system,has been increasingly recognized in recent years as being closely associated with various liver-related diseases,such as hepatic encephalopathy,liver cirrhosis,and hepatocellular carcinoma.Abnormal GABA expression is strongly linked to pathological processes including cognitive impairment and neuroinflammation.Although numerous studies have investigated the mechanistic roles of GABA in neurological complications of liver disease,a systematic overview of the field's research trends,collaborative networks,and emerging hotspots remains lacking.This study employs bibliometric methods to comprehensively map the evolution and frontier topics in GABA and liver-related disease research from 2005 to 2024,aiming to inform future research planning and resource allocation in this area.Methods:English-language publications from 2005 to 2024 related to GABA and liver-related diseases were retrieved from the Web of Science Core Collection.Eligible articles were analyzed using VOSviewer,CiteSpace,and the R package"bibliometrix"to visualize and evaluate contributions by countries/regions,institutions,authors,and journals.Additional analyses included keyword clustering,co-citation analysis,and thematic evolution of research topics.Results:A total of 237 articles were included,contributed by 1 340 authors across 456 institutions in 47 countries,and published in 168 journals.The United States and China are leading contributors in this field.Although countries such as the United Kingdom and Italy had fewer publications,they demonstrated higher average citation counts,indicating strong research quality.Notably,Spain's Centro Investigación Principe Felipe and the research team led by Felipo Vicente exhibited high academic influence.Neurochemistry International and Hepatology were identified as core journals,with Hepatology having the highest impact factor(12.9).Keyword clustering revealed major research focuses including the regulatory role of GABA in the neural mechanisms of hepatic encephalopathy,the impact of liver-related metabolic disorders on neurotransmitter balance,the development and evaluation of GABA receptor-targeted therapeutics,and the function of the GABAergic system in the pathogenesis of hepatocellular carcinoma.As research deepens,the frequency of emerging keywords has diversified,with recent emphasis on terms such as"quality of life,""gene expression,"and"fatty liver disease,"reflecting a shift from fundamental mechanisms to clinical translation and interdisciplinary integration.Conclusion:The relationship between GABA and liver diseases has become a focal point of interdisciplinary research.Investigations have expanded from pathological mechanisms to therapeutic applications,with growing interest in GABA's roles in hepatic encephalopathy,metabolic dysregulation,and tumor progression.Future studies should explore the specific functions of GABA receptor subtypes,promote the development of precision-targeted therapies,and investigate novel mechanisms such as the gut microbiota-GABA metabolism-brain-liver axis to broaden the clinical and translational potential of GABA in neurological,metabolic,and oncological contexts.

Background and Aims:Gamma-aminobutyric acid(GABA),the principal inhibitory neurotransmitter in the central nervous system,has been increasingly recognized in recent years as being closely associated with various liver-related diseases,such as hepatic encephalopathy,liver cirrhosis,and hepatocellular carcinoma.Abnormal GABA expression is strongly linked to pathological processes including cognitive impairment and neuroinflammation.Although numerous studies have investigated the mechanistic roles of GABA in neurological complications of liver disease,a systematic overview of the field's research trends,collaborative networks,and emerging hotspots remains lacking.This study employs bibliometric methods to comprehensively map the evolution and frontier topics in GABA and liver-related disease research from 2005 to 2024,aiming to inform future research planning and resource allocation in this area.Methods:English-language publications from 2005 to 2024 related to GABA and liver-related diseases were retrieved from the Web of Science Core Collection.Eligible articles were analyzed using VOSviewer,CiteSpace,and the R package"bibliometrix"to visualize and evaluate contributions by countries/regions,institutions,authors,and journals.Additional analyses included keyword clustering,co-citation analysis,and thematic evolution of research topics.Results:A total of 237 articles were included,contributed by 1 340 authors across 456 institutions in 47 countries,and published in 168 journals.The United States and China are leading contributors in this field.Although countries such as the United Kingdom and Italy had fewer publications,they demonstrated higher average citation counts,indicating strong research quality.Notably,Spain's Centro Investigación Principe Felipe and the research team led by Felipo Vicente exhibited high academic influence.Neurochemistry International and Hepatology were identified as core journals,with Hepatology having the highest impact factor(12.9).Keyword clustering revealed major research focuses including the regulatory role of GABA in the neural mechanisms of hepatic encephalopathy,the impact of liver-related metabolic disorders on neurotransmitter balance,the development and evaluation of GABA receptor-targeted therapeutics,and the function of the GABAergic system in the pathogenesis of hepatocellular carcinoma.As research deepens,the frequency of emerging keywords has diversified,with recent emphasis on terms such as"quality of life,""gene expression,"and"fatty liver disease,"reflecting a shift from fundamental mechanisms to clinical translation and interdisciplinary integration.Conclusion:The relationship between GABA and liver diseases has become a focal point of interdisciplinary research.Investigations have expanded from pathological mechanisms to therapeutic applications,with growing interest in GABA's roles in hepatic encephalopathy,metabolic dysregulation,and tumor progression.Future studies should explore the specific functions of GABA receptor subtypes,promote the development of precision-targeted therapies,and investigate novel mechanisms such as the gut microbiota-GABA metabolism-brain-liver axis to broaden the clinical and translational potential of GABA in neurological,metabolic,and oncological contexts.

Scientific research is an important part of hospital work,the driving force of hospital construction and development,and the key to the hospital's comprehensive competitiveness and future development potential.Scientific research misconduct,which seriously deviates from the recognized norms of the scientific community,and will cause great harm to groups,society,and the public.It may also lead to the spread of false knowledge,resulting in misconceptions among peers and causing losses.By analyzing the scientific research integrity relationship between clinical doctors and clinical researchers,as well as looking at integrity standards from multiple dimensions,this paper found out the similarities and differences in the extension of integrity between them.Exploring measures to further promote the construction of scientific integrity and ethics,especially increasing the supervisory role of discipline inspection and supervision,which is conducive to the promotion of scientific research in the medical field in China.

Objective:To investigate the clinical value of radiomics based on computed tomography (CT) examination in preoperative differential diagnosis of pancreatic serous cystadenoma (SCA) and mucinous cystadenoma (MCA).Methods:The retrospective case-control study was conducted. The clinicopathological and imaging data of 154 patients with pancreatic cystic neoplasms who were admitted to the First Affiliated Hospital, Zhejiang University School of Medicine from January 2012 to December 2019 were collected. There were 24 males and 130 females, aged (50±13)years. Of the 154 patients, 99 cases were diagnosed as SCA and 55 cases were diagnosed as MCA. All the 154 patients underwent plain and enhanced CT scan of pancreas before operation. The clinical characteristics, radiology features and radiomics features of all patients were collected to construct the clinical characteristics model, radiology model, radiomics model and fused model. The receiver operating characteristic (ROC) curve of each model was drawn, and those constructed models were evaluated by area under the curve (AUC), accuracy, sensitivity, specificity, positive predictive value and negative predictive value. Based on the optimal model, the nomogram was constructed. Observation indicators: (1) establishment and validation of clinical characteristics model; (2) establishment and validation of radiology model; (3) establishment and validation of radiomics model; (4) establishment and validation of fused model; (5) nomogram of fused model. Measurement data with normal distribution were represented as Mean± SD, and comparison between groups was analyzed using the Mann-Whitney U test. Count data were described as absolute numbers or percentages, and comparison between groups was analyzed using the chi-square test or Fisher exact probability. Results:(1) Establishment and validation of clinical characteristics model: 3 clinical characteristics, including age, symptoms and preoperative serum CA19-9, were selected using multinomial logistic linear regression analysis to construct the clinical characteristics model. Result of the multinomial logistic linear regression analysis was expressed by formula ①: clinical characteristics model score=0.635-0.007×age+0.054×clinical symptoms+0.108×preoperative serum CA19-9. The ROC curve for the test dataset of clinical characteristics model was drawn. The AUC, accuracy, sensitivity, specificity, positive predictive value and negative predictive value of clinical characteristics model were 0.611(95% confidence interval as 0.488?0.734, P<0.05), 56.6%, 66.7%, 56.3%, 41.5%, 78.4% for the training dataset and 0.771(95% confidence interval as 0.624?0.919, P<0.05), 77.8%, 63.1%, 88.5%, 80.1%, 76.7% for the test dataset, respectively. (2) Establishment and validation of radiology model: 5 radiology characteristics, including tumor location, the number of tumors, tumor diameter of cross section, lobulated tumor and polycystic tumor (more than 6), were selected using multinomial logistic linear regression analysis to construct the radiology model. Result of the multinomial logistic linear regression analysis was expressed by formula ②: radiology model score=?0.034+0.300×tumor location+0.202×the number of tumors+0.014×tumor diameter of cross section?0.251×lobulated tumor?0.170×polycystic tumor (more than 6). The ROC curve for the test dataset of radiology model was drawn. The AUC, accuracy, sensitivity, specificity, positive predictive value and negative predictive value of radiology model were 0.862(95% confidence interval as 0.791?0.932, P<0.05), 78.8%, 81.8%, 77.5%, 62.8%, 90.2% for the training dataset and 0.853(95% confidence interval as 0.713?0.994), P<0.05), 88.9%, 89.4%, 88.5%, 85.0%, 92.0% for the test dataset, respectively. (3) Establishment and validation of radiomics model: 4 categories of a total 1 067 radiomics features were extracted from 154 patients with pancreatic cystic neoplasms, including 7 first-order histogram features, 53 texture features, 848 wavelet features and 159 local binary pattern features. A total of 896 stable radiomics features were retained to construct the model, based on the condition of intraclass correlation coefficient >0.9. After selected by variance threshold and correlation coefficient threshold, 350 radiomics features were retained. Fifty synthetic radiomics features were constructed based on the original features in order to obtain potential radiomics features, and the total number of radiomics features was 400. After analyzed by the five-fold recursive feature elimination, 22 radiomics features were screened out, including 13 wavelet features, 7 synthetic radiomics features and 2 local binary pattern features. The support vector machine algorithm was used to construct the radiomics model. The penalty coefficient 'C' and parameter 'γ' of the radiomics model were 35.938 and 0.077, respectively. The kernel function of the radiomics model was 'radial basis function kernel'. The ROC curve of radiomics model using 5-fold cross validation was drawn. The average AUC, accuracy, sensitivity, specificity, positive predictive value and negative predictive value of the radiomics model were 0.870 ( P<0.05), 83.1%, 81.8%, 83.8%, 73.8% and 89.2%, respectively. (4) Establishment and validation of fused model: the fused model was constructed after selecting the tumor location and lobulated tumor of radiology characteristics and radiomics score. Result of the multinomial logistic linear regression analysis was expressed by formula ③: fused model socre=?0.154+0.218×tumor location?0.223×lobulated tumor+0.621×radiomics score. The ROC curve for the test dataset of fused model was drawn. The AUC, accuracy, sensitivity, specificity, positive predictive value and negative predictive value of fused model were 0.893(95% confidence interval as 0.828?0.958, P<0.05), 83.7%, 81.8%, 84.5%, 71.1%, 90.9% for the training dataset and 0.966(95% confidence interval as 0.921?0.999, P<0.05), 91.1%, 84.2%, 96.2%, 94.1%, 89.3% for the test dataset, respectively. (5) Nomogram of fused model: the nomogram of fused model was illustrated with the Youden index of 0.416. Conclusion:The prediction model based on the radiomics signature and radiological features extracted from preoperative CT examination can make the differential diagnosis of pancreatic SCA from MCA.

OBJECTIVE: To study the mechanism of tumor necrosis factor( TNF)-α and its receptor( TNFR) signal transduction pathways in regulating cell apoptosis of alveolar macrophage( AM) in coal workers' pneumoconiosis( CWP).METHODS: Twenty-four coal workers with pneumoconiosis at stage Ⅰ were selected as CWP group and four observation subjects exposed to coal were chosen as observation group by using simple random sampling method. The bronchoalveolar lavage fluids of whole-lung lavage of two groups were collected. AMs were separated and purified. Then they were divided into 6 groups: a control group,a superoxide dismutase( SOD) group,a TNF/TNFR group,an anti-TNF-α antibody group,a Caspase-8 suppression group and a nuclear factor-κB( NF-κB) suppression group. The AMs of 6 groups with corresponding treatment were cultivated. After 24 hours,the cells were harvested and proteins extracted. The relative expression of TNF-α,TNFR1,TNFR2,Caspase-8,Caspase-3,NF-κB P50 and NF-κB P65 protein was detected by Western blotting. RESULTS: The protein relative expression of TNF-α,TNFR2,Caspase-8,Caspase-3,NF-κB P50 and NF-κB P65 in CWP group was significantly higher than those in the observation group( P < 0. 05). The protein relative expression of TNF-α,TNFR1,Caspase-8,Caspase-3 and NF-κB P50 in the TNF/TNFR group and the anti-TNF-αantibody group was lower than that of the control group( P < 0. 05). The above indexes in the anti-TNF-α antibody group were lower than that of the NF-κB suppression group( P < 0. 05). The protein relative expression of TNFR1,Caspase-8and Caspase-3 in the TNF/TNFR group was higher than that of the SOD group and the Caspase-8 suppression group( P <0. 05). The protein relative expression of TNFR1,Caspase-8 and NF-κB P50 in the TNF/TNFR group was lower than that of the NF-κB suppression group( P < 0. 05). Among the CWP patients,the relative expression of TNFR2 and NF-κB P65 in the TNF/TNFR group was lower than that of the control group( P < 0. 05),and higher than that of the SOD group( P <0. 05). CONCLUSION: AM apoptosis mediated by TNF-α/TNFR/NF-κB signal transduction pathway plays an important role in the occurrence and development of CWP. The TNF-α/TNFR/NF-κB signal transduction pathways inhibited or blocked at different stages can affect the expression of proteins related to AM apoptosis.