Objective To identify the key factors affecting the risk of medical surges and their coupling relation5 ships,providing strategic support for medical institutions to optimize risk management and emergency governance.Methods 17 influencing factors were determined based on WSR theory,and an expert scoring method was employed to assess the impact strength among the factors.The DEMATEL method was applied to calculate the centrality,cau5 sality,influence,and being influenced degrees of the influencing factors.The ISM method was used to construct a hierarchical structure of the influencing factors related to medical surge risks,thereby revealing the connections and interaction mechanisms among these factors.Results Seven critical influencing factors were identified,including the crisis decision-making capacity and leadership effectiveness of emergency managers,the completeness of the emer5 gency system and dynamic execution capabilities,and the cross-departmental coordination mechanism and com5 mand collaboration efficiency.Deep driving factors and coupling pathways were also revealed.Conclusion The risk of medical surges exhibits multi-factorial coupling cascade effects;attention should be directed towards the construc5 tion of mid-to-deep level mechanisms such as information systems,institutional frameworks,and organizational management,to enhance targeted capabilities and systemic resilience in risk governance.

Objective To explore the coupling mechanism between medical surge response resources and the spread of secondary risks during public health emergencies,as well as the effectiveness of relevant interventions.Methods Based on complex network theory,a dual-layer network model of medical resources and secondary events was constructed.The interactive feedback between medical resource status and secondary event risk,as well as the effects of network structure,were analyzed through MATLAB simulations,REPAST agent-based modeling,and mean-field analysis.Results Simulation and prediction results show that an increase in first-layer resource-deficient nodes significantly raises the activation rate and transmission speed of secondary events,while the clustering and spread of secondary events in the second layer,in turn,intensify resource depletion,creating a negative feedback loop.Mean-field analysis indicates a nonlinear positive correlation between the adequacy of medical resources and the likelihood of secondary events.Network structure analysis reveals that when the average node degree exceeds 8,resource allocation efficiency improves markedly.Conclusion There exists a dynamic coupling and bidirectional feedback relationship between medical resource status and secondary event risks.Enhancing the flexible allocation and responsiveness of medical resources,improving multi-sectoral collaborative monitoring and coordinated regulation,optimizing network connectivity and coordination mechanisms for resource distribution,and establishing dynamic monitoring and tiered early warning systems are key strategies for strengthening the resilience of healthcare systems and effectively containing the spread of secondary events.

Objective To define the conceptual connotation of network dynamic collaboration capacity in medical surge response and construct its theoretical model.Methods A mixed concept analysis method was employed,integrating multidisciplinary literature and collecting empirical evidence through semi-structured expert interviews to extract the concept of network dynamic collaboration capacity in medical surge response.By integrating complex systems,network science,synergetics,and dynamic capability theory,and combining the interview results,the study used the analogy of flood control in hydraulic engineering to develop a"network-dynamic-collaboration"triangular capacity theoretical model.Results It reveals one antecedents(sudden external shocks have led to an abnormal and continuous surge in medical demand),six core attributes(information interconnection accessibility,dynamic resource adaptability,risk perception responsiveness,multi-party collaborative interactivity,service process adaptability elasticity,and learning iterative evolution),and four consequences(mitigation of crowding risk,protection of service continuity,minimization of crisis spillover,and enhancement of system resilience)for the network dynamic collaboration capacity in medical surge response.The theoretical model elucidates the coupling mechanisms among network structural resilience,dynamic regulation processes,and collaborative co-evolution in resisting medical surge.Conclusion The new concept and theoretical model proposed in this study deepen the understanding of medical surge response system mechanisms and offer a theoretical framework and practical guidance for strengthening the full-chain resilience of health emergency systems.

Objective To investigate the gene expression profile of cervical exfoliated cells from woman treated by artificial cycle,and their potential association with endometrial receptivity in order to screen specific biomarkers closely related to the receptivity.Methods A total of 19 female patients were enrolled from those preparing for frozen embryo transfer(FET)at the Reproductive Center of First Medical Center of Chinese PLA General Hospital from February 2024 to October 2024.Under the artificial cycle frozen embryo transfer protocol,the endometrial tissues were collected on the 4th day after progesterone administration(P+4)to verify their endometrial receptivity status.Additionally,cervical exfoliated cells were collected on the 4th day(P+4)and the 6th day(P+6)after progesterone administration.RNA sequencing(RNA-Seq)was used to detect gene expression profiles.Differentially expressed genes(DEGs)were identified using the criteria of|log2fold change|＞1 and a false discovery rate(FDR)＜0.05,followed by bioinformatics analysis.The protein-protein interaction(PPI)network of DEGs was constructed using R software(4.4.1)and analyzed with gene ontology(GO)and Kyoto encyclopedia of genes and genomes(KEGG)analyses.The candidate genes were identified based on the PPI network using Cytoscape software.Quantitative reverse transcription PCR(RT-qPCR)was employed to validate the target candidate genes both in vitro and in vivo.Results The rsERT confirmed that all 19 women were in state of endometrial receptivity at P+6.RNA-Seq identified 3 458 DEGs in cervical exfoliated cells between P+4 and P+6.The up-regulated DEGs were mainly enriched in the pathways associated with immune response and cell differentiation,and the down-regulated ones were mainly enriched in the pathways associated with lipid metabolism and cell proliferation.Using maximal clique Centrality(MCC)algorithm in the PPI network,the top 20 genes were selected.Among them,6 genes,such as IFIT2,OASL,MX1,RSAD2,IFIT1 and IFIT3,tied for the first place,and the 6 genes all belong to interferon-stimulated genes(ISGs).qRT-PCR indicated that the above 6 genes showed significantly higher expression levels in the cervical exfoliated cells at the P+4 stage than the cells at the P+6 stage(P＜0.05).Conclusion There are changes in the expression levels of the genes related to immunity and cytoskeleton remodeling in cervical exfoliated cells during the endometrial receptivity phase.The decrease in the expression of ISGs may serve as a potential biomarker for endometrial receptivity.

Objective To identify the key factors affecting the risk of medical surges and their coupling relation5 ships,providing strategic support for medical institutions to optimize risk management and emergency governance.Methods 17 influencing factors were determined based on WSR theory,and an expert scoring method was employed to assess the impact strength among the factors.The DEMATEL method was applied to calculate the centrality,cau5 sality,influence,and being influenced degrees of the influencing factors.The ISM method was used to construct a hierarchical structure of the influencing factors related to medical surge risks,thereby revealing the connections and interaction mechanisms among these factors.Results Seven critical influencing factors were identified,including the crisis decision-making capacity and leadership effectiveness of emergency managers,the completeness of the emer5 gency system and dynamic execution capabilities,and the cross-departmental coordination mechanism and com5 mand collaboration efficiency.Deep driving factors and coupling pathways were also revealed.Conclusion The risk of medical surges exhibits multi-factorial coupling cascade effects;attention should be directed towards the construc5 tion of mid-to-deep level mechanisms such as information systems,institutional frameworks,and organizational management,to enhance targeted capabilities and systemic resilience in risk governance.

Objective To explore the coupling mechanism between medical surge response resources and the spread of secondary risks during public health emergencies,as well as the effectiveness of relevant interventions.Methods Based on complex network theory,a dual-layer network model of medical resources and secondary events was constructed.The interactive feedback between medical resource status and secondary event risk,as well as the effects of network structure,were analyzed through MATLAB simulations,REPAST agent-based modeling,and mean-field analysis.Results Simulation and prediction results show that an increase in first-layer resource-deficient nodes significantly raises the activation rate and transmission speed of secondary events,while the clustering and spread of secondary events in the second layer,in turn,intensify resource depletion,creating a negative feedback loop.Mean-field analysis indicates a nonlinear positive correlation between the adequacy of medical resources and the likelihood of secondary events.Network structure analysis reveals that when the average node degree exceeds 8,resource allocation efficiency improves markedly.Conclusion There exists a dynamic coupling and bidirectional feedback relationship between medical resource status and secondary event risks.Enhancing the flexible allocation and responsiveness of medical resources,improving multi-sectoral collaborative monitoring and coordinated regulation,optimizing network connectivity and coordination mechanisms for resource distribution,and establishing dynamic monitoring and tiered early warning systems are key strategies for strengthening the resilience of healthcare systems and effectively containing the spread of secondary events.

Objective To define the conceptual connotation of network dynamic collaboration capacity in medical surge response and construct its theoretical model.Methods A mixed concept analysis method was employed,integrating multidisciplinary literature and collecting empirical evidence through semi-structured expert interviews to extract the concept of network dynamic collaboration capacity in medical surge response.By integrating complex systems,network science,synergetics,and dynamic capability theory,and combining the interview results,the study used the analogy of flood control in hydraulic engineering to develop a"network-dynamic-collaboration"triangular capacity theoretical model.Results It reveals one antecedents(sudden external shocks have led to an abnormal and continuous surge in medical demand),six core attributes(information interconnection accessibility,dynamic resource adaptability,risk perception responsiveness,multi-party collaborative interactivity,service process adaptability elasticity,and learning iterative evolution),and four consequences(mitigation of crowding risk,protection of service continuity,minimization of crisis spillover,and enhancement of system resilience)for the network dynamic collaboration capacity in medical surge response.The theoretical model elucidates the coupling mechanisms among network structural resilience,dynamic regulation processes,and collaborative co-evolution in resisting medical surge.Conclusion The new concept and theoretical model proposed in this study deepen the understanding of medical surge response system mechanisms and offer a theoretical framework and practical guidance for strengthening the full-chain resilience of health emergency systems.

Tic disorder is a chronic neuropsychiatric disorder with complex etiology and diverse phenotypes,and its incidence has been increasing significantly in recent years.Most scholars believe that abnormalities in the cortico-striatal-thalamo-cortical circuit and its interconnected brain regions are closely related to the development of tic disorder.Chinese materia medica intervention in tic disorders is characterized by multi-targets,multi-mechanisms and holistic nature,and has a good prospect for research application.This article summarized the experimental studies of TCM compound intervention in tic disorder in recent years,which have shown that TCM compounds could reduce the damage of nerve cells through the regulation of neurotransmitters,inflammatory response,immune function and the"colony-gut-brain axis"to improve and prevent tic disorder,which could provide a reference for the research and development of new medicines for tic disorder and for the clinical research.

Tic disorder is a chronic neuropsychiatric disorder with complex etiology and diverse phenotypes,and its incidence has been increasing significantly in recent years.Most scholars believe that abnormalities in the cortico-striatal-thalamo-cortical circuit and its interconnected brain regions are closely related to the development of tic disorder.Chinese materia medica intervention in tic disorders is characterized by multi-targets,multi-mechanisms and holistic nature,and has a good prospect for research application.This article summarized the experimental studies of TCM compound intervention in tic disorder in recent years,which have shown that TCM compounds could reduce the damage of nerve cells through the regulation of neurotransmitters,inflammatory response,immune function and the"colony-gut-brain axis"to improve and prevent tic disorder,which could provide a reference for the research and development of new medicines for tic disorder and for the clinical research.

Objective To investigate the distribution and drug resistance characteristics of pathogens in donors and recipients undergoing simultaneous pancreas-kidney transplantation (SPK). Methods Clinical data of 231 pairs of donors and recipients undergoing SPK were analyzed retrospectively. The pathogens of samples from donors and recipients were identified by VITEK-2 analyzer, and drug sensitivity test was performed by K-B method. The source distribution and composition ratio of pathogens in donor and recipient samples, distribution characteristics of multi-drug resistant organism, infection of recipients and drug resistance characteristics of pathogens were analyzed. Results A total of 395 strains of pathogens were cultured from 1 294 donor samples, and the detection rate was 30.53%. Gram-negative bacteria mainly consisted of klebsiella pneumoniae, Gram-positive bacteria mainly comprised staphylococcus aureus, and fungi primarily included candida albicans, respectively. In total, 2 690 strains of pathogens were cultured from 10 507 recipient samples, and the detection rate was 25.60%. Gram-negative bacteria mainly consisted of pseudomonas maltophilia, Gram-positive bacteria primarily comprised enterococcus faecalis, and fungi mainly included candida albicans, respectively. Among 395 pathogens of donors, 15 strains of methicillin-resistant staphylococcus aureus (MRSA), 16 strains of extended-spectrum β-lactamase (ESBL) positive drug-resistant bacteria, 8 strains of carbapenem-resistant pseudomonas aeruginosa (CR-PA), 21 strains of carbapenem-resistant acinetobacter baumannii (CR-AB), 2 strains of carbapenem-resistant enterobacteriaceae (CRE) and 1 strain of multiple-drug/pan-drug resistant pseudomonas aeruginosa (MDR/PDR-PA) were identified. Among 2 690 strains of recipient pathogens, 73 strains of ESBL positive drug-resistant bacteria, 44 strains of CR-PA, 31 strains of CR-AB and 3 strains of MDR/PDR-PA were detected. One recipient developed donor-derived infection, 69 cases of pneumonia, 52 cases of urinary tract infection, 35 cases of abdominal infection and 2 cases of hematogenous infection were reported within postoperative 1 year. Gram-negative bacteria were resistant to certain antibiotics. Gram-positive bacteria were sensitive to vancomycin. Fungi were sensitive to amphotericin B. Conclusions Gram-negative bacteria are the main pathogens of SPK recipients, which are resistant to certain antibiotics. Empirical use of antibiotics can be delivered before culture results are obtained. Subsequently, sensitive antibiotics should be chosen according to the culture results to improve the survival rate of SPK recipients.