ObjectiveThis study leverages structural data from antigen-antibody complexes of the influenza A virus neuraminidase (NA) protein to investigate the spatial recognition relationship between the antigenic epitopes and antibody paratopes. MethodsStructural data on NA protein antigen-antibody complexes were comprehensively collected from the SAbDab database, and processed to obtain the amino acid sequences and spatial distribution information on antigenic epitopes and corresponding antibody paratopes. Statistical analysis was conducted on the antibody sequences, frequency of use of genes, amino acid preferences, and the lengths of complementarity determining regions (CDR). Epitope hotspots for antibody binding were analyzed, and the spatial structural similarity of antibody paratopes was calculated and subjected to clustering, which allowed for a comprehensively exploration of the spatial recognition relationship between antigenic epitopes and antibodies. The specificity of antibodies targeting different antigenic epitope clusters was further validated through bio-layer interferometry (BLI) experiments. ResultsThe collected data revealed that the antigen-antibody complex structure data of influenza A virus NA protein in SAbDab database were mainly from H3N2, H7N9 and H1N1 subtypes. The hotspot regions of antigen epitopes were primarily located around the catalytic active site. The antibodies used for structural analysis were primarily derived from human and murine sources. Among murine antibodies, the most frequently used V-J gene combination was IGHV1-12*01/IGHJ2*01, while for human antibodies, the most common combination was IGHV1-69*01/IGHJ6*01. There were significant differences in the lengths and usage preferences of heavy chain CDR amino acids between antibodies that bind within the catalytic active site and those that bind to regions outside the catalytic active site. The results revealed that structurally similar antibodies could recognize the same epitopes, indicating a specific spatial recognition between antibody and antigen epitopes. Structural overlap in the binding regions was observed for antibodies with similar paratope structures, and the competitive binding of these antibodies to the epitope was confirmed through BLI experiments. ConclusionThe antigen epitopes of NA protein mainly ditributed around the catalytic active site and its surrounding loops. Spatial complementarity and electrostatic interactions play crucial roles in the recognition and binding of antibodies to antigenic epitopes in the catalytic region. There existed a spatial recognition relationship between antigens and antibodies that was independent of the uniqueness of antibody sequences, which means that antibodies with different sequences could potentially form similar local spatial structures and recognize the same epitopes.

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.

Objective: To explore the relationship between cardiorespiratory fitness and executive function in Chinese adolescents, so as to provide a reference for promoting the overall development of Chinese adolescents physical and mental health. Methods: From September to December 2022, a total of 5 018 adolescents aged 13 to 18 years from Shanghai, Suzhou, Taiyuan, Wuyuan, Xingyi, and Urumqi were selected by stratified cluster sampling method to assess cardiorespiratory fitness and executive function. Pearson s correlation and linear hierarchical regression were performed to analyze the relationship between cardiorespiratory fitness and executive functions. Results: Among the sample of adolescents, maximal oxygen consumption (VO 2max ) was negatively correlated with the refreshing(1-back, 2-back) and conversion executive function responses ( r=-0.07, -0.12, -0.12, P <0.01). Linear regression analysis showed that VO 2max was negatively correlated with the reaction times of the refreshing(1-back, 2-back) and conversion functions ( B=-2.99, -6.44, -1.69, P <0.01). Conclusions Higher cardiorespiratory fitness among adolescents is associated with better performance in executive function. Teenagers should strengthen high intensity cardiopulmonary endurance exercise to promote the improvement of executive function.

Abstract Executive function is an advanced cognitive process aimed at the flexible coordination, optimization, and control of the cognitive processes of task solving in order to accomplish a specific task, ensuring that the individual produces effective behaviors, including inhibitory control, working memory, and cognitive flexibility. Given the sensitivities and specificities that characterize an individual s physical and mental development during adolescence, this period is critical for the development of executive function in adolescents. In the paper, the influencing factors of adolescents executive function development are systematically described from three dimensions, namely, biology, environment and lifestyle; by analyzing the mechanisms and differences in the effects of different influencing factors, this editorial provides a scientific basis for adolescents executive function improvement and intervention.

Objective To explore the cognitive load level and influencing factors of emergency nurses.Methods Using convenience sampling method,48 nurses in emergency department of China-Japan Friendship Hospital from April to May 2022 were selected as research objects.General data were collected and total cognitive load and three different types of cognitive load were measured.Results Regression analysis showed that nurse-patient relationship was influencing factor of total cognitive load of nurses in emergency department(β=6.202,P=0.007),the noisy working environment was the influencing factor of the internal cognitive load(β=1.042,P<0.001),and the living situation(sharing with others)was the influencing factor of the external cognitive load(β=-3.917,P=0.006).The factors of associated with cognitive load were not found.Conclusion The total cognitive load and the three types of cognitive load of nurses in emergency department are high.Nursing managers can reduce the cognitive load of nurses in emergency department by adjusting related influencing factors,so as to improve nursing work efficiency.

Objective:Operational efficiency and influencing factors of China's basic medical insurance system from 2020 to 2021 is conducted to provide reference for improving the operational efficiency and optimizing the input-output relationship.Methods:The super-efficiency SBM model based on unexpected output and the Malmquist index are used to measure the static and dynamic efficiency of resident medical insurance in 31 provinces in China,and Tobit regression analysis is employed to analyze the influencing factors.Results:The overall operational efficiency of resident medical insurance still needs improvement.The operational efficiency of resident medical insurance in the central and western regions is lower than that in the eastern region,and the gap is significant.Different levels and regions have differentiated main constraints on the operational efficiency of resident medical insurance.In terms of dynamic efficiency,the total factor productivity of resident medical insurance operation shows an increasing trend,mainly due to technological progress.In terms of influencing factors,the degree of aging,the level of medical expenses and the level of medical insurance supervision have a significant impact on the operational efficiency.Suggestions:Efforts should be made to bridge regional disparities,promote the equitable development of medical insurance,reasonably control the level of medical expenses,strengthen the supervision of medical insurance funds,and implement active aging policies.

Objective:To evaluate the reliability and validity of the Chinese version of HEMO-FISS-QoL(HF-QoL) questionnaire (HF-QoL-C) in the Chinese population with hemorrhoids.Methods:From November 2021 to November 2022, a self-constructed general information questionnaire, HF-QoL-C, and the 36-item short form health survey (SF-36), Goligher classification, and Giordano severity of hemorrhoid symptom questionnaire (GSQ) were used to conduct a questionnaire survey on 760 hemorrhoid patients in the anorectal department of six hospitals. The data was analyzed for reliability and validity using SPSS 21.0 and AMOS 26.0 software.Results:The Cronbach's α coefficient of HF-QoL-C and its dimension ranged from 0.831 to 0.960, and the split coefficient was 0.832-0.915. Four common factors were extracted through principal component exploratory factor analysis. Confirmatory factor analysis indicated acceptable structural validity( χ2/ df=8.152, RSMEA=0.097, CFI=0.881, IFI=0.881, NFI=0.867). HF-QoL-C was correlated with SF36 and GSQ( r=-0.694, 0.501, both P<0.01). There were differences in the total score and dimensional scores of HF-QoL-C between surgical and drug treated patients, different grades of Goligher classification for hemorrhoidal disease, and different ranges of hemorrhoid prolapse (all P<0.001). No ceiling effect was found in the total score and the scores of each dimension(0.3%-2.0%). There was a floor effect in both psychological function and sexual activity dimensions (16.7%, 35.1%). Conclusion:HF-QoL-C has good reliability and validity, which can be used to measure the quality of life of Chinese hemorrhoid patients.

Medical mutual aid is an important component of multi-level medical security system. West China Second University Hospital of Sichuan University led the establishment of the pediatric specialty alliance " West China Women and Children Alliance". Based on customized and inclusive mutual insurance product " Family Doctor Mutual Aid Plan", the alliance implemented key links such as mutual aid product forms, patient risk protection, institutional financing and hematopoiesis, and distribution of benefits to all parties, explored innovative mutual aid funding, payment, and incentive mechanisms, forming a closed-loop pediatric tiered diagnosis and treatment service system with the Mutual Aid Plan as the core. This system operated continuously under the " Four-in-One" framework, stimulating the integration of medical insurance and service supply systems while enhancing the synergistic effect between mutual insurance and social security. It has formed a distinctive health-centered multi-level medical security system within the alliance, and could provide reference for the construction and exploration of hierarchical diagnosis and treatment system.

Objective:To investigate the hot topics and trends of implementation science in the transformation of clinical practice guidelines, in order to provide ideas and references for clinical managers to reasonably apply and implement scientific promotion guidelines.Methods:CiteSpace6.2.R3 software was used to visualize the literature, which retrieved from the core database of Web of Science, including the number of articles, countries and high-frequency keywords and keyword clustering and emergence for visual analysis, etc.Results:A total of 4 593 articles were included in the final analysis. Since 1993, the number of published papers had increased year by year. The hot topics focused on primary care, attitudes, knowledge translation, clinical trials, risk factors and machine learning. The research trends included older adults and artificial intelligence.Conclusions:The rapid development of implementation science in guideline translation research suggests that scholars from various countries, especially hospital administrators should reasonably apply implementation science framework to integrate evidence into clinical practice, and promote the implementation of clinical practice guidelines.

Cancer is one of the deadliest diseases affecting the health of human beings. With limited therapeutic options available, complementary and alternative medicine has been widely adopted in cancer management and is increasingly becoming accepted by both patients and healthcare workers alike. Chinese medicine characterized by its unique diagnostic and treatment system is the most widely applied complementary and alternative medicine. It emphasizes symptoms and ZHENG (syndrome)-based treatment combined with contemporary disease diagnosis and further stratifies patients into individualized medicine subgroups. As a representative cancer with the highest degree of malignancy, pancreatic cancer is traditionally classified into the "amassment and accumulation". Emerging perspectives define the core pathogenesis of pancreatic cancer as "dampness-heat" and the respective treatment "clearing heat and resolving dampness" has been demonstrated to prolong survival in pancreatic cancer patients, as has been observed in many other cancers. This clinical advantage encourages an exploration of the essence of dampness-heat ZHENG (DHZ) in cancer and investigation into underlying mechanisms of action of herbal formulations against dampness-heat. However, at present, there is a lack of understanding of the molecular characteristics of DHZ in cancer and no standardized and widely accepted animal model to study this core syndrome in vivo. The shortage of animal models limits the ability to uncover the antitumor mechanisms of herbal medicines and to assess the safety profile of the natural products derived from them. This review summarizes the current research on DHZ in cancer in terms of the clinical aspects, molecular landscape, and animal models. This study aims to provide comprehensive insight that can be used for the establishment of a future standardized ZHENG-based cancer animal model.
Animals ; Humans ; Medicine, Chinese Traditional ; Hot Temperature ; Pancreatic Neoplasms/therapy* ; Models, Animal ; Syndrome