Objective To explore the application effect of a standardized management method based on failure mode and effect analysis （FMEA） in optimizing the whole-process quality control system of the intravenous admixture service （PIVAS）. Methods The quality control management system of the PIVAS was optimized by establishing six quality control groups led by the head nurse, with full participation of pharmacy, nursing, and logistical staff, ensuring comprehensive coverage and traceability of all quality control links. Each group conducted risk priority number （RPN） scoring for potential failure modes in their respective quality control processes, and targeted improvement measures were formulated based on the scoring results. The RPN values of failure modes and quality control-related evaluation indicators before and after implementation were compared to achieve closed-loop management. Results After one year of management, the RPN values of the six major failure modes significantly decreased compared to those before implementation （P<0.05）. The compounding error rate dropped to 0.13%, the dispensing error rate decreased to 0.95%, the compounding efficiency increased to 98%, the delivery time was shortened by 0.45 h per batch, the intervention rate for irrational prescriptions rose to 94.87%, satisfaction improved to 96.78%, and the participation rate of quality control personnel reached 95.36% （P<0.05）. Conclusion FMEA-based identification of potential failure modes in the whole-process quality control system of the IVAS, combined with risk quantification and targeted interventions, significantly reduced high-risk failure modes, improved compounding accuracy and efficiency, and ensured the safety of clinical intravenous medication and the effectiveness of healthcare quality management.

Objective To explore the application effect of a standardized management method based on failure mode and effect analysis （FMEA） in optimizing the whole-process quality control system of the intravenous admixture service （PIVAS）. Methods The quality control management system of the PIVAS was optimized by establishing six quality control groups led by the head nurse, with full participation of pharmacy, nursing, and logistical staff, ensuring comprehensive coverage and traceability of all quality control links. Each group conducted risk priority number （RPN） scoring for potential failure modes in their respective quality control processes, and targeted improvement measures were formulated based on the scoring results. The RPN values of failure modes and quality control-related evaluation indicators before and after implementation were compared to achieve closed-loop management. Results After one year of management, the RPN values of the six major failure modes significantly decreased compared to those before implementation （P<0.05）. The compounding error rate dropped to 0.13%, the dispensing error rate decreased to 0.95%, the compounding efficiency increased to 98%, the delivery time was shortened by 0.45 h per batch, the intervention rate for irrational prescriptions rose to 94.87%, satisfaction improved to 96.78%, and the participation rate of quality control personnel reached 95.36% （P<0.05）. Conclusion FMEA-based identification of potential failure modes in the whole-process quality control system of the IVAS, combined with risk quantification and targeted interventions, significantly reduced high-risk failure modes, improved compounding accuracy and efficiency, and ensured the safety of clinical intravenous medication and the effectiveness of healthcare quality management.

Objective To systematically identify the key genes regulating the exit from na?ve pluripotency in embryonic stem cells(ESCs)in order to provide novel targets and theoretical insights into the mechanisms for pluripotency transition and early cell fate determination.Methods Nanog-green fluorescent protein(Nanog-GFP)reporter-labeled ESCs were infected with a genome-wide Brie knockout library,and further cultured under leukemia inhibitory factor/serum(LIF/S)conditions for 14 d.Flow cytometry was used to sort Nanog-GFP?(na?ve-state)and Nanog-GFP-(primed state)cell populations,followed by genomic DNA extraction and high-throughput sequencing.Model-based Analysis of Genome-wide CRISPR/Cas9 Knockout(MAGeCK)was applied to identify differential genes between GFP?/Input,GFP?/Input,and GFP?/GFP? groups.Metascape and Gene Set Enrichment Analysis(GSEA)were conducted for functional enrichment analysis.Then the obtained candidate genes were employed to construct knockout models,and their roles were assessed through cell morphology observation,Nanog-positive rate detection,colony formation assays,and pluripotency gene expression analysis.Results The GFP?/Input screening revealed 2 921 negatively regulated genes(mainly enriched in basic life processes,such as RNA metabolism and cell cycle)and 1 393 positively regulated genes(enriched in the processes of nervous system development,carbohydrate metabolism,and vascular system development).In the GFP?/Input screening,2 765 negatively regulated genes(enriched in RNA metabolism,cell cycle,and other fundamental processes)and 1 303 positively regulated genes(enriched in neural development,cell survival,and endothelial migration)were identified.The GFP?/GFP? comparison identified 1 001 negatively regulated genes[involved in stress response and inhibition of mitogen-activated protein kinase(MAPK)signaling]and 983 positively regulated genes[related to fibroblast growth factor/extracellular signal-regulated kinase(FGF/ERK)signaling pathway and glucose metabolism).These genes,were not only known pluripotency regulators(e.g.,Nanog,Nr5a2,Klf2,Klf4)and exit-associated genes(e.g.,Gata6,Grb2,Zeb1,Fgfr1),but also some novel candidates(e.g.,Dmrt1,Rxra,Zbtb14 and Tmem41b).Functional validation showed that transient knockout of Dmrt1,Tmem41b,and Hic2 significantly increased the proportion of Nanog? cells(P<0.01),suggesting their role in suppressing ground-state exit.ESCs with stable Dmrt1 knockout exhibited a more na?ve-state phenotype,presenting compact,dome-shaped colonies,with increased ratio of undifferentiated colonies(P<0.01),up-regulation of ground-state markers(Nanog,Nr5a2,Dppa3,P<0.01),and down-regulation of primed-state markers(Fgf5,Lefty1,Dnmt3b,P<0.01).Rescue experiments for Dmrt1 expression reversed these above phenotypes.Conclusion A candidate gene set regulating exit from na?ve pluripotency in ESC is screened out and identified with genome-wide CRISPR.Our findings implicate Dmrt1 plays a critical role in promoting the exit.

In recent years,the application of immunotherapy has improved the prognosis of relapsed/refractory(R/R)B cell-acute lympho-blastic leukemia(B-ALL).Blinatumomab,Inotuzumab ozogamicin(InO),and chimeric antigen receptor(CAR)T-cell therapies are the three major immunotherapeutic agents approved for the treatment of R/R B-ALL.This new strategy incorporates immunotherapy into the first line of treatment to reduce the adverse effects of chemotherapy,prolong survival,and expand treatment options for elderly patients.This art-icle discusses new approaches for incorporating immunotherapeutic agents into firstline B-ALL treatment regimens,exploring the potential value of chemotherapy-free regimens in specific patient subgroups,to provide guidance for clinical practice.

Objective To clarify the evidence of the frequency and risk factors for falls in knee osteoarthritis(KOA)of adults by meta-analysis.Methods Computerized searches of the CNKI,VIP,Wanfang data,CBM,PubMed,Cochrane Library,Embase,Web of Science were conducted for literature on risk factors for falls in adults with KOA from the inception of the databases to August 2024.After literature screening,data extraction,and quality evaluation,RevMan 5.4 software was used for Meta-analysis.Results A total of 26 articles were involved.Meta-analysis result showed that the rate of falls was 29.0％.Factors associated with increased risk of falls included being female(OR=1.35),decreased lower limb muscle strength(OR=1.72),decreased knee flexion muscle strength(OR=7.05),decreased static posture stability(OR=1.28),opioid use(OR=1.79),antidepressant use(OR=1.69),frequent stair climbing(OR=7.58),combined neurological disease(OR=1.77),history of falls(OR=3.29)and fear of falling(OR=2.54).Conclusion The rate of falls of patients with KOA is high.The adults with KOA who are women,have lower muscle strength of lower limbs and knee flexion muscle strength,poorer static posture stability,use opioids,antidepressant,frequent stair climbing,combined neurological disorders,previous falls in the past year and fear of falls are at higher risk of falls.Healthcare professionals should dynamically assess and detect the risk of falls in the patients with KOA and adopt targeted,individualized interventions to prevent falls.

BACKGROUND:Agomelatine is a clinically proven treatment for neuropsychiatric symptoms,such as anxiety and depression.Furthermore,our previous study has demonstrated that agomelatine ameliorates cognitive behaviors,hippocampal synaptic plasticity,and brain pathology in a mouse model of Alzheimer's disease.However,it remains unclear whether agomelatine can improve anxiety and depression-like behaviors in Alzheimer's disease model mice. OBJECTIVE:To investigate the improving effects of agomelatine on anxiety-and depression-like behaviors in APP/PS1 transgenic mice and its underlying molecular mechanisms. METHODS:(1)Eighteen APP/PS1 transgenic mice were randomly divided into model control group(n=9)and model intervention group(n=9).Another wild-type mice were randomized into control group(n=9)and intervention group(n=9).Model intervention group and intervention group were intraperitoneally injected with 10 mg/kg agomelatine per day for 31 continuous days.Behavioral experiments,including the elevated cross maze and forced swimming tests,and mRNA sequencing of the hippocampus were then performed.(2)Mouse hippocampal neuronal cell lines(HT22)and brain microvascular endothelial cell lines(bEnd.3)were cultured and divided into four groups:blank group without any drug,drug group with 20 μmol/L agomelatine,model group with 10 μmol/L β-amyloid 1-42,and experimental group with 10 μmol/L β-amyloid 1-42+20 μmol/L agomelatine.After 24 hours of incubation,protein expression of S416p-tau and S9p-GSK3β in HT22 cells was detected by immunoblotting,and protein expression of low-density lipoprotein receptor-related protein 1 and glycosylation end-product receptor in bEnd.3 cells was detected by immunoblotting. RESULTS AND CONCLUSION:In the elevated plus maze test,the time spent in the open arms(P＜0.01)and the entries into open arms(P＜0.05)in the mice of model control group were evidently lower than those in the control group,whereas those were obviously increased in the model intervention group compared with the model control group(P＜0.05).Forced swimming test results showed that the immobile time exhibited a marked increase in the model control group compared with the control group(P＜0.05),but it was significantly decreased in the model intervention group compared with the model control group(P＜0.05).Hippocampal tissue mRNA sequencing showed that agomelatine enhanced the expression of low-density lipoprotein receptor-related protein 1 in the hippocampus of APP/PS1 mice.Western blot analysis revealed that the level of S416p-tau in HT22 cells was higher in the model group than the blank group(P＜0.05),while it was markedly decreased in the experimental group compared with the model group(P＜0.05);the level of S9p-GSK3β in HT22 cells was higher in the drug group than the blank group(P＜0.05)as well as higher in the experimental group than the model group(P＜0.05).Moreover,the expression of low-density lipoprotein receptor-related protein 1 in bEnd.3 cells was higher in the experimental group than the model group(P＜0.05).To conclude,agomelatine can alleviate anxiety-and depression-like behaviors in Alzheimer's disease mice by promoting the clearance of β-amyloid and phosphorylated tau.

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 Exploring the components of complex scenarios of healthcare surges triggered by major epidemics to provide a theorical basis for building resilience in healthcare organizations.Methods A hybrid analysis method is used to summarize macro-meso-micro multi-level and multi-source heterogeneous information,extract the elements of complex scenarios of medical surge and evaluate the rationality.Fault Tree Analysis method is used to clarify the logical relationship between various scenario elements and construct scenario reasoning paths.Results 10 scenario states,11 disaster-bearing,24 emergency management and 23 scenario results are summarized and extracted to form the key elements of complex surge scenarios.Among them,M4 expansion and coordinated scheduling of key positions,B2 conventional drug inventory emergency/insufficient core treatment drugs,B emergency medical material transportation breakage,S3 disease symptom spectrum shift to severe disease,R13 prevention and control awareness laxity,and M5 media information dissemination management are the key driving factors that promote a major turning point in the scenario.The most positive scenario result is the orderly operation of the medical service system,and the most negative scenario result is the paralysis of the medical service system.Conclusion Medical institutions need to improve emergency plans based on the complex evolution scenarios of medical surges and agile governance capabilities targeting key turning points,focus on dynamically expanding and scheduling personnel in key positions,strengthen material rotation and reserve mechanisms,maintain smooth emergency logistics channels,and improve efficient management of media and public opinion,so as to comprehensively improve overall resilience.

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.