Objective To investigate and analyze the occupational stress levels and influencing factors among radiation workers in China, and provide a reference for alleviating occupational stress and promoting mental health. Methods Using the general situation questionnaire, Effort-Reward Imbalance questionnaire, and radiation protection knowledge questionnaire, a convenience sampling method was adopted to investigate the occupational stress of 243 radiation workers in Liaoning, Fujian, Guangdong, and Xinjiang provinces. The independent samples t-test, one-way analysis of variance, chi-square test, and binary logistic regression were used to analyze the influencing factors. Results The average score of Effort-Reward Imbalance was 0.97 ± 0.22, and 100 (41.15%) radiation workers had occupational stress. There were significant differences in the detection rate of occupational stress among radiation workers of different ages, working years in radiation positions, monthly incomes, daily sleep durations, and daily working hours (P < 0.05). Logistic regression analysis identified daily working hours as a factor contributing to occupational stress. Conclusion The occupational stress among radiation workers in China is relatively severe. It is recommended to pay attention to the associated risks and implement targeted intervention measures to reduce the impact of occupational stress.

BACKGROUND:Solute carrier family 1 member 5(SLC1A5)plays a potential role in a variety of diseases,but the exact mechanism of action is unclear.The construction of stable SLC1A5 overexpression and knockdown cell models can provide a powerful experimental tool for in-depth study of the exact role and mechanism of SLC1A5 in diseases and the discovery of potential therapeutic targets. OBJECTIVE:To construct lentiviral vectors for overexpression and knockdown of mouse SLC1A5 and establish stable transfected RAW264.7 cell lines,so as to provide an experimental foundation for further investigation of the role of SLC1A5 in inflammation. METHODS:Primers were designed and synthesized based on the SLC1A5 gene sequence,and the gene segment was amplified using polymerase chain reaction.Subsequently,the target gene segment was directionally inserted into the GV492 vector plasmid,which had been digested with AgeI/NheI enzymes,to construct recombinant lentiviral plasmids.Positive clones were further selected,and their sequences were confirmed.The pHelper1.0 plasmid vector and pHelper2.0 plasmid vector,along with the target plasmid vector,was co-cultured with 293T cells for transfection,resulting in the production and titration of lentiviral stocks.Furthermore,RAW264.7 cells were cultured in vitro,and the working concentration of puromycin was determined.Lentiviruses were separately co-cultured with RAW264.7 cells,and transfection efficiency was determined by measuring fluorescence intensity.Stable transfected cells were selected using puromycin,and real-time fluorescence quantitative PCR and western blot assay were employed to assess the gene and protein expression levels of SLC1A5 in stably transfected cell lines. RESULTS AND CONCLUSION:(1)Sequencing results indicated a perfect match between the sequencing and target sequences,confirming the successful construction of recombinant lentiviral vectors.(2)The titer for the overexpression SLC1A5 lentivirus was 1×109 TU/mL,while the titer for the knockdown SLC1A5 lentivirus was 3×109 TU/mL.(3)The working concentration of puromycin for RAW264.7 cells was determined to be 3 μg/mL.(4)The optimal conditions for transfecting RAW264.7 cells with overexpression/knockdown expression of SLC1A5 lentivirus involved the use of HiTransG P transfection enhancer with a multiplicity of infection value of 50.(5)A significant upregulation of the gene and protein expression levels of SLC1A5 was detected in cell lines stably overexpressing SLC1A5,while gene and protein expression levels of SLC1A5 were significantly decreased in the knockdown stable cell lines.These findings indicate that lentiviral vectors for mouse SLC1A5 overexpression and knockdown have been successfully constructed and a stably transfected RAW264.7 cell line has been obtained.

Lung transplantation is the optimal treatment for end-stage lung diseases and can significantly improve prognosis of the patients. However, postoperative complications such as infection, rejection, ischemia-reperfusion injury, and other challenges (like shortage of donor lungs) , limit the practical application of lung transplantation in clinical practice. Chinese research teams have been making continuous efforts and have achieved breakthroughs in basic research on lung transplantation by integrating emerging technologies and cutting-edge achievements from interdisciplinary fields, which has strongly propelled the development of this field. This article will comprehensively review the academic progress made by Chinese research teams in the field of lung transplantation in 2024, with a focus on the achievements of Chinese teams in basic research on lung transplantation. It aims to provide innovative ideas and strategies for key issues in the basic field of lung transplantation and to help China's lung transplantation cause reach a higher level.

Objective: To summarize strategies for improving childhood hypertension, so as to provide evidencebased recommendations for poliymaking and practice childhood hypertension management in China. Methods: From March to April 2024, child health stakeholders from five districts in Hangzhou were selected using a combination of stratified and convenience sampling methods. Data were analyzed using a groundedtheory approach. During the indepth interview phase, six policymakers were interviewed. Focus group discussions were conducted with school administrators, healthcare providers, and parents, comprising a total of 62 participants. Results: Through threelevel coding, 116 initial categories were identified(e.g., "trend of younger age" "difficulty in behavior change"), 35 main categories (e.g., "higher incidence compared to the past" "caused by comprehensive influencing factors"), and 12 core categories (e.g., "epidemic status" "influencing factors"). Finally, the cognitive status, problem analysis, and management strategies of children hypertension were constructed. Conclusion Effective prevention and control of childhood hypertension requires coordinated efforts among governments, schools, families, and society to establish a comprehensive management system, with dynamic monitoring and evaluation to optimize policy implementation.

Lung cancer （LC） is a significant global public health issue， with both its incidence and mortality rates ranking among the highest worldwide. The age-standardized incidence and mortality rates are increasing annually， posing a serious threat to the life and health of LC patients. Radical surgical resection is the primary treatment for malignant lung tumors. However， postoperative multidimensional functional impairments， including respiratory， mucosal， and psychological functions， are common. These impairments not only reduce patients' quality of life and affect their treatment tolerance and duration， but also negatively correlate with prognosis， facilitating disease recurrence and metastasis. At present， postoperative functional dysfunction after LC surgery remains a key clinical challenge that urgently needs to be addressed. There is a lack of standardized and regulated postoperative rehabilitation treatment management and traditional Chinese medicine （TCM） differentiation and treatment strategies for LC. Focusing on the core underlying pathogenesis of "Qi sinking" after LC surgery， and guided by the classical TCM theory of "lungs governing Qi"， this study， based on the core concept of the "five perspectives on treatment" theory， innovatively proposes the respiratory dysfunction as the core pathogenesis of "Qi sinking in the chest" during the rapid rehabilitation phase， mucosal dysfunction as the core pathogenesis of "Yin deficiency and Qi sinking" during the postoperative adjuvant treatment phase， and the psychological dysfunction as the core pathogenesis of "Qi sinking with emotional constraint" during the consolidation phase. Accordingly， stage-specific dynamic functional protection strategies are constructed. In the rapid rehabilitation phase， the strategy emphasizes tonifying Qi and uplifting sinking Qi， with differentiation and treatment based on the principle of ''descending before ascending''. In the adjuvant treatment phase， the approach focuses on nourishing Yin and uplifting Qi， with prescription combinations that integrate unblocking and tonification. In the consolidation phase， the strategy aims to resolve constraint and uplift Qi， with clinical treatment emphasizing a combination of dynamic and static methods. At each stage of functional rehabilitation， clinical differentiation and treatment should support healthy Qi and eliminate pathogenic factors simultaneously. This study is the first to propose the concept of postoperative functional protection in TCM， offering a new approach for TCM differentiation and treatment in the full-cycle， stage-based， and dynamic protection of postoperative function in LC patients. It is expected to contribute to the construction and development of an integrated TCM-Western medicine comprehensive program for cancer prevention and treatment in China.

Objective To construct a key technical indicator system for in-hospital treatment and nursing of patients with nuclear radiation injury, and provide a basis for the implementation of such treatment and nursing. Methods The draft of the key technical indicator system for in-hospital treatment and nursing of patients with nuclear radiation injury was determined by literature review, case study, and field investigation. The indicators of the system were determined through two rounds of Delphi consultation and using the precedence chart method. According to the criteria of indicator evaluation, the reliability of expert opinions, and the opinions of the research group, the indicators were refined and evaluated. Results Twenty experts were included for two rounds of consultation via mailed inquiries, with a 100% effective response rate in both rounds. The expert authority coefficients were both 0.945, and the Kendall’s W values were 0.347 and 0.448, respectively (P < 0.05). Following the expert consultations, 1 indicator was deleted, 12 indicators were added, and 6 indicators were modified. The key technical indicator system for in-hospital treatment and nursing of patients with nuclear radiation injury established in this study included 4 first-level indicators, 17 second-level indicators, and 73 third-level indicators. The means of importance assignment for all indicators were > 4.00, and the coefficients of variation were < 0.25. Conclusion The key technical indicator system for in-hospital treatment and nursing of patients with nuclear radiation injury established in this study is scientifically rigorous and practically grounded. The indicators demonstrate strong professional relevance and provide important guidance for in-hospital treatment and nursing of patients with nuclear radiation injury.

Cardiovascular disease (CVD), chronic kidney disease (CKD), and metabolic disorders are the 3 major chronic diseases threatening human health, which are closely related and often coexist, significantly increasing the difficulty of disease management. In response, the American Heart Association (AHA) proposed a novel disease concept of “cardiovascular-kidney-metabolic (CKM) syndrome” in October 2023, which has triggered widespread concern about the co-treatment of heart and kidney diseases and the prevention and treatment of metabolic disorders around the world. This review posits that effectively managing CKM syndrome requires a new and multidimensional paradigm for diagnosis and risk prediction that integrates biological insights, advanced technology and social determinants of health (SDoH). We argue that the core pathological driver is a “metabolic toxic environment”, fueled by adipose tissue dysfunction and characterized by a vicious cycle of systemic inflammation and oxidative stress, which forms a common pathway to multi-organ injury. The at-risk population is defined not only by biological characteristics but also significantly impacted by adverse SDoH, which can elevate the risk of advanced CKM by a factor of 1.18 to 3.50, underscoring the critical need for equity in screening and care strategies. This review systematically charts the progression of diagnostic technologies. In diagnostics, we highlight a crucial shift from single-marker assessments to comprehensive multi-marker panels. The synergistic application of traditional biomarkers like NT-proBNP (reflecting cardiac stress) and UACR (indicating kidney damage) with emerging indicators such as systemic immune-inflammation index (SII) and Klotho protein facilitates a holistic evaluation of multi-organ health. Furthermore, this paper explores the pivotal role of non-invasive monitoring technologies in detecting subclinical disease. Techniques like multi-wavelength photoplethysmography (PPG) and impedance cardiography (ICG) provide a real-time window into microcirculatory and hemodynamic status, enabling the identification of early, often asymptomatic, functional abnormalities that precede overt organ failure. In imaging, progress is marked by a move towards precise, quantitative evaluation, exemplified by artificial intelligence-powered quantitative computed tomography (AI-QCT). By integrating AI-QCT with clinical risk factors, the predictive accuracy for cardiovascular events within 6 months significantly improves, with the area under the curve (AUC) increasing from 0.637 to 0.688, demonstrating its potential for reclassifying risk in CKM stage 3. In the domain of risk prediction, we trace the evolution from traditional statistical tools to next-generation models. The new PREVENT equation represents a major advancement by incorporating key kidney function markers (eGFR, UACR), which can enhance the detection rate of CKD in primary care by 20%-30%. However, we contend that the future lies in dynamic, machine learning-based models. Algorithms such as XGBoost have achieved an AUC of 0.82 for predicting 365-day cardiovascular events, while deep learning models like KFDeep have demonstrated exceptional performance in predicting kidney failure risk with an AUC of 0.946. Unlike static calculators, these AI-driven tools can process complex, multimodal data and continuously update risk profiles, paving the way for truly personalized and proactive medicine. In conclusion, this review advocates for a paradigm shift toward a holistic and technologically advanced framework for CKM management. Future efforts must focus on the deep integration of multimodal data, the development of novel AI-driven biomarkers, the implementation of refined SDoH-informed interventions, and the promotion of interdisciplinary collaboration to construct an efficient, equitable, and effective system for CKM screening and intervention.

ObjectiveEndothelial cell dysfunction being the core link. This study explores the molecular mechanism of Danshen Tongluo formula in treating coronary artery disease-dominated panvascular disease with endothelial cell changes as the core through animal experiments and single-cell transcriptome sequencing. MethodsA rat model of coronary artery disease-dominated panvascular disease was established by ligating the left anterior coronary artery. Rats were randomized into a blank group， a model group， and a Danshen Tongluo formula （28 mg·kg^-1·d^-1） group. The efficacy was evaluated by examining the cardiac ultrasound， determination of the plasma level of N-terminal pro-brain natriuretic peptide， and pathological staining. After single-cell sequencing， SingleR package， public datasets， and related literature were used for annotation of the cells. Cell chat was used for intercellular communication and ligand-receptor analysis， and scmetabolism was used for metabolic analysis of endothelial cells. ResultsAnimal experiments showed that Danshen Tongluo formula reduced the N-terminal pro-brain natriuretic peptide （ NT-proBNP ） level （P<0.05）， ameliorated myocardial cell damage and fibrosis， and increase left ventricular ejection fractions （LVEF） in the rat model of heart failure after myocardial infarction（P<0.05）. Single-cell sequencing results showed that Danshen Tongluo formula increased the proportion of arterial endothelial cells， venous endothelial cells， and capillary-arterial endothelial cells， while reducing the proportion of capillary-venous endothelial cells. In addition， this formula increased the interaction intensity of endothelial cells with cardiomyocytes and M1 macrophages and reduced the interaction intensity of endothelial cells with fibroblasts and T cells. Danshen Tongluo formula upregulated CXCL12-CXCR4 signaling in endothelium-B cells and Ptprm-Ptprm signaling in endothelial endothelial cells， while downregulating Mif-（CD74⁺CXCR44） signaling in endothelium-M1 macrophages and Mif-（CD74⁺CD44） signaling in endothelium-M2 macrophages. It reduced the citric acid cycle， oxidative phosphorylation， and glycolysis and increased the glycolysis/oxidative phosphorylation ratio in endothelial cells. GO and KEGG enrichment analysis showed that arterial endothelial cells， venous endothelial cells， and venous capillary endothelial cells can all regulate oxidative phosphorylation， cell adhesion molecules， and tyrosine metabolism. Lymphatic endothelial cells regulate immunity and vascular constriction to participate in the metabolism of various amino acids and fatty acids. ConclusionDanshen Tongluo Formula can ameliorate coronary artery disease-dominated panvascular disease by changing the composition of endothelial cells and regulating the communication between myocardial endothelial cells and non-endothelial cells.

BACKGROUND: Postoperative pulmonary complications (PPCs) are major adverse events in neurosurgical patients. This study aimed to develop and validate machine learning models predicting PPCs after neurosurgery. METHODS: PPCs were defined according to the European Perioperative Clinical Outcome standards as occurring within 7 postoperative days. Data of cases meeting inclusion/exclusion criteria were extracted from the anesthesia information management system to create three datasets: The development (data of Huashan Hospital, Fudan University from 2018 to 2020), temporal validation (data of Huashan Hospital, Fudan University in 2021) and external validation (data of other three hospitals in 2023) datasets. Machine learning models of six algorithms were trained using either 35 retrievable and plausible features or the 11 features selected by Lasso regression. Temporal validation was conducted for all models and the 11-feature models were also externally validated. Independent risk factors were identified and feature importance in top models was analyzed. RESULTS: PPCs occurred in 712 of 7533 (9.5%), 258 of 2824 (9.1%), and 207 of 2300 (9.0%) patients in the development, temporal validation and external validation datasets, respectively. During cross-validation training, all models except Bayes demonstrated good discrimination with an area under the receiver operating characteristic curve (AUC) of 0.840. In temporal validation of full-feature models, deep neural network (DNN) performed the best with an AUC of 0.835 (95% confidence interval [CI]: 0.805-0.858) and a Brier score of 0.069, followed by Logistic regression (LR), random forest and XGBoost. The 11-feature models performed comparable to full-feature models with very close but statistically significantly lower AUCs, with the top models of DNN and LR in temporal and external validations. An 11-feature nomogram was drawn based on the LR algorithm and it outperformed the minimally modified Assess respiratory RIsk in Surgical patients in CATalonia (ARISCAT) and Laparoscopic Surgery Video Educational Guidelines (LAS VEGAS) scores with a higher AUC (LR: 0.824, ARISCAT: 0.672, LAS: 0.663). Independent risk factors based on multivariate LR mostly overlapped with Lasso-selected features, but lacked consistency with the important features using the Shapley additive explanation (SHAP) method of the LR model. CONCLUSIONS: The developed models, especially the DNN model and the nomogram, had good discrimination and calibration, and could be used for predicting PPCs in neurosurgical patients. The establishment of machine learning models and the ascertainment of risk factors might assist clinical decision support for improving surgical outcomes. TRIAL REGISTRATION ChiCTR 2100047474; https://www.chictr.org.cn/showproj.html?proj=128279 .
Adult ; Aged ; Female ; Humans ; Male ; Middle Aged ; Algorithms ; Lung Diseases/etiology* ; Machine Learning ; Neurosurgical Procedures/adverse effects* ; Postoperative Complications/diagnosis* ; Risk Factors ; ROC Curve