Objective To address the safety challenges arising from the rapid development of nuclear energy and technology, assess the current status of health emergency response capabilities in nuclear radiation emergencies, and promote capacity enhancement. Methods A preliminary evaluation system for health emergency response capability in nuclear radiation emergencies was developed based on a literature review. Two rounds of Delphi expert consultation (n = 20) were conducted, and the analytic hierarchy process was employed to establish judgment matrices for assigning indicator weights. Results The finalized system included six primary indicators (radiation protection capability, triage capability, decontamination and evacuation capability, medical treatment capability, radiation detection capability, and radiation dose estimation capability), along with 29 secondary indicators, such as capability for setting up emergency zones, capability for protecting personnel from internal and external contamination, on-site first aid capability, and personal dose monitoring capability. The expert response rate was 0.95, and the expert authority coefficient reached 0.80. The Kendall’s coefficient of concordance was W = 0.288 (P<0.01) for the first round of expert consultation and W = 0.308 (P<0.01) for the second round. Both rounds demonstrated high agreement among experts, and the consultation questionnaires passed reliability and validity tests. Conclusion By integrating qualitative analysis and quantitative calculation, this study developed a scientifically sound and operationally feasible evaluation system. This system will help identify gaps in health emergency response capabilities and provide scientific guidance and a decision-making basis for optimizing emergency plans and improving the level of health emergency response in nuclear radiation emergencies.

Objective To investigate the role of PTGDR2 in the progression of lung adenocarcinoma(LUAD)and its potential as a thera-peutic target in regard to regulating tumor stemness via autophagy.Methods In vitro experiments were conducted by silencing PTGDR2 with siRNA and treating LUAD A549 cells with PGD2 in order to evaluate its effects on cell proliferation,invasion,and stem cell marker expression.Autophagy regulation was further verified by rapamycin treatment.Results Activation of PTGDR2 signaling inhibited A549 cell proliferation and invasion,induced the upregulation of autophagy markers,and reduced the expression of stem cell markers.In con-trast,silencing PTGDR2blocked autophagy and enhanced tumor stemness.Conclusion PTGDR2 inhibits tumor stemness through the activation of autophagy,and therefore has potential as a therapeutic target to overcome drug resistance in LUAD.

Objective:To compare the clinical efficacy of autologous bone grafting or bioceramic bone grafting combined with locking compression plate (LCP) internal fixation in the treatment of Schatzker type II and III tibial plateau fractures.Methods:A retrospective analysis was conducted on 104 patients with Schatzker type II and III tibial plateau fractures who underwent surgical treatment at the Department of Orthopedics, PLA Central Theater Command General Hospital from January 2010 to December 2021. The cohort comprised 55 males and 49 females, with an average age of 49.13±13.80 years (range 18-73 years). All fractures were unilateral: 55 on the left and 49 on the right. According to the Schatzker classification, 59 were Type II and 45 were Type III. Causes of injury included traffic accidents (48 cases), falls from height (3 cases), sprains or falls (45 cases), and other causes (8 cases). During surgery, bioceramic material or allograft bone tissue was implanted into the collapsed tibial plateau region to restore articular surface flatness. Based on graft type, patients were divided into the allograft bone group (63 cases) and the bioceramic group (41 cases). All cases underwent proximal lateral tibial LCP internal fixation. The two groups were compared in terms of operative time, intraoperative blood loss, bone graft volume, length of hospital stay, fracture healing time, and postoperative complications. The Rasmussen radiographic collapse score was used to evaluate fracture reduction, and the Hospital for Special Surgery (HSS) score system was used to assess knee joint function.Results:All patients were followed up for 12(12, 13) months (range 12-16 months). The fracture healing time in the allograft bone group was 13.70±1.36 weeks (range 11-16 weeks), which was significantly shorter than that in the bioceramic group: 14.59±1.73 weeks (range 11-19 weeks) ( t=2.911, P=0.004). The time to full weight-bearing in the allograft group was 15.0(14.0, 17.0) weeks (range 13-23 weeks), which was shorter than the 16.0 (15.5, 18.5) weeks (range 12-24 weeks) in the bioceramic group, showing a statistically significant difference ( Z=-3.019, P=0.002). At 12 months postoperatively, the Rasmussen radiographic collapse score was 1(0, 1) in the bioceramic group, significantly lower than the 1(1, 2) score in the allograft group ( Z=-2.083, P=0.037). No statistically significant differences were observed between the two groups in bone graft volume, surgical duration, intraoperative blood loss, hospitalization duration, or HSS scores at 6 and 12 months postoperatively ( P>0.05). The complication rate was 6.3% (4/63) in the allograft group and 2.4% (1/41) in the bioceramic group, with no statistically significant difference (χ 2=0.830, P=0.362). Conclusions:For Schatzker type II and III tibial plateau fractures, the use of allograft bone or bioceramic combined with LCP internal fixation can achieve good results. Allograft bone has advantages in terms of fracture healing speed and early weight-bearing recovery, while bioceramic is more effective in maintaining joint surface stability.

China emerges as a major country in nuclear energy development and the application of nuclear and radiologic technology. The diagnosis and treatment of acute radiation syndrom (ARS) caused by external irradiation represent a core function in the country′s medical rescue of nuclear and radiological emergencies. Clinically, ARS manifests hematopoietic, gastrointestinal, cutaneous, and central nervous system syndromes, with specific clinical manifestations, signs, severity, and prognosis strongly correlated with radiation dose. China has established a number of national and provincial centers for treating radiation-induced damage. Nevertheless, most medical staff have limited experience in ARS treatment. This consensus presents a summary of recent experience in treating ARS of China. In combination with recommendations from international organizations such as the World Health Organization (WHO), this consensus proposes key evidence of critical clinical issues of ARS, covering all links in the rescue of external irradiation-induced ARS. Initially, clinical diagnosis, syndromes, and severe degrees should be determined based on clinical symptoms and dose estimates. It is necessary to normalize clinical treatment measures for hematopoietic recovery, gastrointestinal injury treatment, infection control, symptomatic treatment, and multi-organ function preservation. To this end, this consensus offers cautions. This consensus provides principles of treatment with traditional Chinese medicine, psychological intervention, and follow-up. Additionally, it highlights multidisciplinary collaboration. It is recommended that this consensus be applied in relevant treatment centers.

Objective:To investigate the pathogen distribution, temporal trends in the rates of antimicrobial resistance, and susceptibility of bloodstream isolates and comparatively explore the epidemiological characteristics of bloodstream infections in hematology departments across 56 healthcare facilities in Guangdong Province from 2020 to 2024.Methods:A multicenter analysis was conducted to evaluate the constituent ratio of different pathogens isolated from clinical isolate data from bloodstream specimens in hematology, respiratory, and intensive care unit (ICU) departments across 56 healthcare facilities in Guangdong Province (2020-2024), and antimicrobial resistance trends in pathogens with high-detection rate over 5 years were assessed. Carbapenem-resistant Gram-negative organisms (CRO) were randomly sampled for carbapenemase gene detection and in vitro antimicrobial susceptibility tests with novel antimicrobial agents.Results:From 2020 to 2024, a total of 8 968, 6 440, and 25 511 bloodstream isolates were identified in the hematology, respiratory, and ICU departments, respectively, across 56 participating facilities in Guangdong Province, with significant differences in the pathogen constituent ratio among departments ( P<0.001). Notably, the hematology department demonstrated a predominance of Escherichia coli (24.1%), Klebsiella pneumoniae (17.5%), Pseudomonas aeruginosa (11.7%), coagulase-negative Staphylococci (15.2%), and Staphylococcus aureus (5.1%). In the resistance analysis, the rates of meropenem resistance of Escherichia coli and Klebsiella pneumonia increased from 6.7% and 5.8% (2020) to 14.0% and 15.8% (2024), respectively. Conversely, Pseudomonas aeruginosa exhibited a declining trend in the rate of meropenem resistance (6.2% to 1.9%) and imipenem (10.2% to 6.1%) during the same period. Acinetobacter baumannii demonstrated a biphasic resistance pattern to common antimicrobial agents, characterized by an initial decline, followed by a rebound. In this study, the susceptibility rates to conventional antimicrobial agents were significantly higher in Staphylococcus aureus versus coagulase-negative Staphylococci, with no glycopeptide- or linezolid-resistant strains detected. Notably, the prevalence of vancomycin-resistant Enterococcus faecium increased from 0 in 2020 to 23.1% in 2024. CRO carbapenemase phenotypes through active surveillance revealed that 80% Escherichia coli isolates were carrying blaNDM, 90% Klebsiella pneumoniae isolates were carrying blaKPC, 10% Pseudomonas aeruginosa isolates were carrying blaVIM, and 100% Acinetobacter baumannii were carrying blaOXA-23. The results of the antimicrobial susceptibility test in CRO revealed that carbapenem-resistant Escherichia coli (CRECO) demonstrated a 0 resistance rate to tigecycline, polymyxin B, and aztreonam/avibactam, whereas carbapenem-resistant Klebsiella pneumoniae exhibited a 0 resistance rate to aztreonam/avibactam, ceftazidime/avibactam, and imipenem/relebactam. Carbapenem-resistant Pseudomonas aeruginosa exhibited a 95.0% susceptibility rate to amikacin and polymyxin B, with a 45.0% resistance rate to ceftazidime/avibactam. In contrast, carbapenem-resistant Acinetobacter baumannii demonstrated complete susceptibility (100.0%) to sulbactam/durlobactam (MIC90=2 μg/ml), whereas eravacycline showed MIC50 and MIC90 values of 1 and 2 μg/ml, respectively. Conclusion:The pathogen constituent ratio of bloodstream isolates differed significantly among hematology, respiratory, and ICU departments. Notably, although CRO exhibited an escalating prevalence, it sustained high susceptibility to novel antimicrobial agents.

Postoperative infection of internal fixation of closed fractures the lower limbs in adults represents a devastating complication, characterized by diagnostic challenges, prolonged treatment duration and high disability rates. Current management of these infections faces multiple challenges, such as difficulties in early accurate diagnosis, and various controversies about the treatment plan, leading to poor overall diagnosis and treatment results. To address these issues, based on evidence-based medicine and principles with emphasis on scientific rigor, clinical applicability and innovation, the Trauma Branch of the Chinese Medical Association, Orthopedic Branch of the Chinese Medical Doctor Association, Orthopedics Branch of the Chinese Medical Association, and Trauma Orthopedics and Polytrauma Group of the Resuscitation and Emergency Committee of the Chinese Medical Doctor Association have collaboratively organized a panel of relevant experts to develop the Guideline for diagnosis and treatment of infection after internal fixation of closed lower limb fractures in adults ( version 2025). The guideline proposed 10 recommendations, aiming to provide a foundation for standardized diagnosis and treatment of postoperative infection in adults with closed lower limb fractures.

Objective:To develop and validate machine learning-based radiomics models using preoperative CT images for individualized prediction of mitotic index (MI) in patients with gastrointestinal stromal tumors (GIST).Methods:The study was a case-control study. The data of 348 GIST patients confirmed by pathology were retrospectively collected from two independent medical centers: the Affiliated Hospital of Qingdao University (center 1) and Shandong Provincial Hospital Affiliated to Shandong First Medical University (center 2), covering the period from January 2013 to June 2018. Patients from center 1 were divided into a training cohort (176 cases) and an internal validation cohort (75 cases) at a ratio of 7∶3 using random sampling. Patients from center 2 served as an independent external validation cohort (97 cases). The primary endpoint was MI, categorized into high MI (145 cases) and low MI (203 cases) groups. Radiomic features were extracted from the portal venous phase images of preoperative contrast-enhanced CT scans. Five machine learning algorithms, including logistic regression, support vector machine, random forest, decision tree, and extreme gradient boosting (XGBoost),were employed to construct MI prediction models. The optimal model was identified using receiver operating characteristic curves. An individualized prediction model was developed by integrating the the optimal machine learning model combined with selected independent clinical factors, and the importance of features was visualized using Shapley Additive Explanation (SHAP) analysis. Patients were followed up, and Kaplan-Meier curves along with log-rank tests were used to evaluate recurrence-free survival (RFS) differences between the predicted high MI and low MI groups.Results:Among the five constructed machine learning models, the XGBoost model demonstrated the best predictive performance, with area under the curve (AUC) of 0.809 (95% CI 0.738-0.872), 0.693 (95% CI 0.571-0.809), and 0.718 (95% CI 0.605-0.822) in the training cohort, internal validation cohort, and external validation cohort, respectively. An individualized prediction model combining the XGBoost model with independent clinical factors (tumor location and tumor size) was developed. The model achieved AUC of 0.843 (95% CI 0.785-0.899), 0.791 (95% CI 0.680-0.894), and 0.777 (95% CI 0.678-0.861) in the training cohort, internal validation cohort, and external validation cohort, respectively. SHAP analysis indicated that radiomic features had the highest predictive impact. In both the training cohort and internal validation cohort, the RFS of patients predicted to be in the high MI group was lower than that of the low MI group, with statistically significant differences ( χ2=14.58, 9.52, both P<0.001). However, there was no statistically significant difference in RFS in the external validation set ( χ2=6.18, P=0.080). Conclusions:The optimal XGBoost model based on radiomic features extracted from preoperative portal venous phase CT images, when combined with clinical factors, can effectively predict the MI of GIST patients.

Objective:To investigate the value of habitat radiomic features based on gadolinium ethoxybenzyl diethylenetriamine pentaacetic acid (Gd-EOB-DTPA)-enhanced MRI in establishing a predictive model for cytokeratin 19 (CK19) expression in hepatocellular carcinoma (HCC) and to evaluate its role in prognostic risk stratification.Methods:This multicenter case-control study retrospectively enrolled 489 patients with pathologically confirmed HCC who underwent Gd-EOB-DTPA-enhanced MRI between June 2016 and June 2024. Among them, 346 patients from the First Affiliated Hospital of Soochow University were divided into a training cohort ( n=245) and an internal test cohort ( n=101) via stratified sampling at a 7∶3 ratio. And 143 patients from Nantong Third Hospital Affiliated to Nantong University served as an external validation cohort. The training cohort included 53 CK19-positive and 192 CK19-negative patients. The internal test cohort included 21 CK19-positive and 80 CK19-negative patients. The external validation cohort included 30 CK19-positive and 113 CK19-negative patients. Univariate logistic regression analysis was performed to identify potential factors associated with CK19 expression, and a clinical-radiologic model was constructed. The k-means clustering algorithm was applied to segment target HCC lesions into 3 subregions. Radiomic features were extracted and selected from these habitat subregions. Habitat radiomics models were constructed for the arterial phase (AP), portal venous phase, hepatobiliary phase (HBP), and combined phases (CP). Multivariate logistic regression analysis identified independent clinical and radiologic predictors of CK19 expression, and the optimal habitat model score was integrated to build a clinical-radiologic-habitat combined model. The area under the receiver operating characteristic curve (AUC) was used to evaluate model predictive performance. Recurrence-free survival (RFS) was analyzed using the Kaplan-Meier method and the differences in survival curves were compared with the log-rank test. Results:Univariate logistic regression analysis revealed that alpha-fetoprotein (AFP) ( OR=2.629, 95% CI 1.412-4.896, P=0.002), AP enhancement ( OR=3.636, 95% CI 1.642-8.052, P=0.001), AP peritumoral enhancement ( OR=2.219, 95% CI 1.084-4.542, P=0.029), and HBP peritumoral hypointensity ( OR=2.010, 95% CI 1.004-4.021, P=0.049) were potential factors associated with CK19 expression, which were incorporated into the clinical-radiologic model. In the internal and external validation cohorts, the AUC of the clinical-radiologic model was 0.690 (95% CI 0.590-0.778) and 0.650 (95% CI 0.565-0.727), respectively. The habitat radiomics model based on CP images demonstrated the highest performance. It achieved AUC of 0.729 (95% CI 0.622-0.836) and 0.725 (95% CI 0.607-0.842) in the internal and external validation cohorts, respectively. Multivariate analysis identified AFP ( OR=2.494, 95% CI 1.163-5.348, P=0.019), AP enhancement ( OR=5.230, 95% CI 1.868-14.643, P=0.002) and habitat radiomics model score ( OR=4.105, 95% CI 2.643-6.368, P<0.001) as independent predictors of CK19 positivity. Based on these factors, a combined clinical-radiologic-habitat combined model was established. The clinical-radiologic-habitat combined model achieved AUCs of 0.767 (95% CI 0.671-0.846) and 0.730 (95% CI 0.649-0.801) in the internal and external validation cohorts, respectively. Significant differences in RFS were observed between the CK19-positive group (25.1 month) and CK19-negative group (51.0 month) as predicted by the clinical-radiologic-habitat model ( χ2=4.17, P=0.041). Conclusion:The clinical-radiologic-habitat combined model based on Gd-EOB-DTPA-enhanced MRI habitat radiomics demonstrates good predictive performance for CK19 expression in HCC and offers valuable prognostic stratification for clinical practice.

Objective:To investigate the value of coronary CTA (CCTA)-based traditional features and radiomics of plaque in the identification of culprit lesions that caused acute myocardial infarction (AMI).Methods:This was a retrospective multicenter study. From July 2016 to November 2023, a total of 344 patients from the Affiliated Hospital of Qingdao University (training cohort, n=184), Shandong Provincial Hospital Affiliated to Shandong First Medical University (validation cohort, n=88) and Qilu Hospital of Shandong University (test cohort, n=72) who received percutaneous coronary intervention (PCI) due to AMI and underwent CCTA within 48 hours of AMI were enrolled. The culprit plaques and non-culprit plaques were identified using a combination of electrocardiogram, CCTA, and angiographic findings. The vessel, plaque location, plaque type, Coronary Artery Disease-Reporting and Data System (CAD-RADS) score, high-risk plaque characteristics, plaque length, plaque volume, and burden were analyzed, and 1 904 radiomics features were extracted for each plaque. The traditional imaging model, the radiomics model, and the combined model were established by using multivariate Logistic regression analysis. The area under the receiver operating characteristic curve (AUC) was used to evaluate the performance of each model in identifying culprit lesions. The DeLong test was used for the comparison of AUC between every two models. The net reclassification index (NRI) was used to evaluate the incremental value of the combined model to the traditional imaging model and the radiomics model. The decision curve analysis (DCA) was used to assess the clinical net benefit of these models. A correlation heatmap was used to evaluate the correlation between the radiomics score and traditional CCTA factors. The interpretable analysis of the decision process of the combined model was performed by the Shapley Additive exPlanations (SHAP). Results:In the validation cohort and the test cohort, the AUC of the traditional imaging model developed by the vessel, plaque type, positive remodeling and CAD-RADS score was 0.898 (95% CI 0.869-0.922) and 0.881 (95% CI 0.848-0.910), respectively. The radiomics model developed by six radiomics features was 0.863 (95% CI 0.831-0.891) and 0.863 (95% CI 0.827-0.864), respectively. The AUC of the combined model was 0.930 (95% CI 0.905-0.950)and 0.919 (95% CI 0.889-0.942), respectively. In the validation cohort and the test cohort, the AUC of the combined model was higher than that of the traditional imaging model ( Z=4.013, 4.272, P<0.001) and that of the radiomics model ( Z=4.819, 3.784, P<0.001), respectively. In the validation cohort, the combined model yielded an NRI of 20.43% (95% CI 10.43%-30.44%, P<0.001) and 20.21% (95% CI 9.62%-30.80%, P<0.001) for identifying culprit lesions compared with the traditional imaging model and the radiomics model, respectively. In the test cohort, the combined model yielded an NRI of 28.05% (95% CI 16.72%-39.38%, P<0.001) and 23.57% (95% CI 13.58%-33.56%, P<0.001) for identifying culprit lesions compared with the traditional imaging model and the radiomics model, respectively. DCA showed the combined model had the highest clinical net benefit. The correlation heatmap showed the radiomics score was not correlated or only weakly correlated with traditional CCTA factors. SHAP indicated the radiomics and CAD-RADS score contributed significantly to the model. Conclusion:The CCTA-based traditional features and radiomics of plaque have favorable performance for the identification of culprit plaques in patients with AMI.

Objective Emergency response to public health emergencies constitutes a vital component of the modernization of national governance systems and capacities, directly impacting national security, social stability, and public health. This study aims to analyze the key issues and research hotspots in the field of emergency response to public health emergencies, providing theoretical foundations and practical guidance for formulating scientific and effective emergency strategies and policies. Ultimately, it seeks to enhance the nation’s capability to respond to public health emergencies and safeguard public health. Methods Using core journals indexed in the China National Knowledge Infrastructure (CNKI) database as the data source, 1094 journal articles in the field of emergency response to public health emergencies in China from 2003 to September 2024 were selected as the research sample. Citespace visualization software was employed to organize and analyze the research process in the field of emergency response to public health emergencies. Results The current research in this field predominantly involves small-scale cooperation, and the research process can be divided into four stages. The research in the emerging stage mainly focuses on the themes of emergency mechanism and emergency management, the development stage mainly centers on the themes of emergency capacity improvement and system exploration, the outbreak stage emphasizes the themes of COVID-19 and epidemic prevention and control, and the sustainable development stage highlights collaborative governance and informatization. Conclusion The COVID-19 pandemic has accelerated the development of research in this field. Currently, the field shows a continuous growth, with an increasing volume of publications. The focus of current research has shifted towards collaborative governance and the study of assessment tools, aiming to enhance the efficiency and effectiveness in responding to public health emergencies. Moreover, the field is advancing toward more systematic and comprehensive research. However, there is still a need to strengthen scientific communication and collaboration.