The increasing electrification of urban transportation,i.e.,subways and electric vehicles(EV),brings more interactions between the power system and transportation system and further results in fault propagation across...The increasing electrification of urban transportation,i.e.,subways and electric vehicles(EV),brings more interactions between the power system and transportation system and further results in fault propagation across them.To analyze vulnerability of the coupling system under extreme events,this paper establishes a multi-layer urban electric-transportation interdependent network(ETIN)model.First,a weighted coupled metro-road traffic network(CTN)model and network path planning approach are proposed.A prospect theory-based failure load redistribution(FLR)method is further established to account for uncertainty of TN link capacity affected by power supply.Second,topology and emergency control strategy of power network(PN)are modeled,followed by formulation of multi-layer ETIN model.In particular,the inter-layer fault propagation from PN to TN is modeled based on power supply correlation strength,while from TN to PN is modeled based on traffic flow.A few indexes are then defined to quantify vulnerability of ETIN under deliberate attack.Finally,the proposed method is verified on an electric-transportation system to show influence of fault propagations within ETIN on its vulnerability under extreme events.展开更多
The combustion and detonation processes of energetic materials exhibit remarkable complexity and ultra-fast transient characteristics.While reactive molecular dynamics has been extensively employed to investigate the ...The combustion and detonation processes of energetic materials exhibit remarkable complexity and ultra-fast transient characteristics.While reactive molecular dynamics has been extensively employed to investigate the reaction dynamics of energetic materials,its utility is often constrained to capturing only fundamental reaction events and species information,thereby limiting mechanistic investigations of complex reaction pathways.To elucidate the topological features of energetic material reaction networks and identify critical reaction pathways with high fidelity,this study presents ReacNetwork-an advanced large-scale reaction network analysis methodology that synergistically integrates complex network theory with molecular simulation techniques.Specifically,we have developed a multi-dimensional feature screening protocol based on node centrality metrics and K-shell decomposition algorithms.Takingα-Hexahydro-1,3,5-trinitro-1,3,5-triazine(α-RDX)as the subject,we successfully constructed a comprehensive high-temperature thermal decomposition reaction network consisting of 1,134 distinct chemical species and 3,626 elementary reactions.Through systematic application of community detection algorithms and global topological feature extraction techniques,we achieved effective dimensionality reduction and successfully identified the dominant reaction pathway within theα-RDX thermal decomposition network.The computational results not only validate the well-established initial reaction mechanism dominated by N-NO2 homolytic bond cleavage,but also provide unprecedented visualization ofα-RDX framework ring-opening dynamics and subsequent radical chain propagation networks.展开更多
This study explores the core characteristics,dynamic progression of the depression-anxiety-stress network among Chinese higher vocational college freshmen and its association with life satisfaction,and identifies key ...This study explores the core characteristics,dynamic progression of the depression-anxiety-stress network among Chinese higher vocational college freshmen and its association with life satisfaction,and identifies key nodes and critical intervention points.Participants were 295 higher vocational college freshmen(male=137;M=18.52,SD=0.69)completing two follow-up surveys(5-month interval).Measures included depression-anxiety-stress symptoms and life satisfaction,analyzed via cross-sectional and binary cross-lagged panel network analysis.The results showed that“Easily agitated”was the central node(strength=1.519,EI=1.967);“Irritable”and“Mouth Dryness”were top predictors(Out-EI=1.101,1.100),with depressive symptoms as the convergence hub.“Easily agitated”had the strongest direct negative impact on life satisfaction(cross-cluster out-predictability=−0.653).This study elucidates depression-anxietystress network mechanisms in higher vocational freshmen,providing a theoretical framework and targeted intervention guidance(e.g.,focusing on somatic and emotional nodes).展开更多
Background:Amid the global rise in adolescent sedentary behavior and psychological distress,extant research has largely focused on variable-level associations,neglecting symptom-level interactions.This study applies n...Background:Amid the global rise in adolescent sedentary behavior and psychological distress,extant research has largely focused on variable-level associations,neglecting symptom-level interactions.This study applies network analysis,aims to delineate the interconnections among sedentary time,social support,social exclusion,and psychological distress in Chinese students,and to identify core and bridge symptoms to inform targeted interventions.Methods:This study employed a cross-sectional design to investigate the complex relationships among sedentary behavior,social support,social exclusion,and psychological distress among Chinese students.The research involved 459 high school and university students,using network analysis and mediation models to examine these relationships.Results:Network analysis revealed that the network had a density of 58.33%and an average edge weight of 0.11.In terms of centrality,stress had the highest expected influence(EI=1.135),acting as the core amplifier in the network.Sedentary behavior demonstrated the highest bridging expected influence,functioning as a critical bridge for cross-community transmission.Conversely,friend support showed the lowest bridging EI with a negative value,indicating its effectiveness in blocking cross-community diffusion and alleviating symptoms.Conclusion:With stress acting as the most influential“core engine”within the symptom network and sedentary behavior serving as the key“bridge”for cross-community transmission,interventions should first target stress to weaken the overall symptom cascade,followed by reducing sedentary behavior or enhancing friend support to disrupt cross-community pathways,thereby achieving a core-bridge dual blockade.展开更多
This paper investigates the reliability of internal marine combustion engines using an integrated approach that combines Fault Tree Analysis(FTA)and Bayesian Networks(BN).FTA provides a structured,top-down method for ...This paper investigates the reliability of internal marine combustion engines using an integrated approach that combines Fault Tree Analysis(FTA)and Bayesian Networks(BN).FTA provides a structured,top-down method for identifying critical failure modes and their root causes,while BN introduces flexibility in probabilistic reasoning,enabling dynamic updates based on new evidence.This dual methodology overcomes the limitations of static FTA models,offering a comprehensive framework for system reliability analysis.Critical failures,including External Leakage(ELU),Failure to Start(FTS),and Overheating(OHE),were identified as key risks.By incorporating redundancy into high-risk components such as pumps and batteries,the likelihood of these failures was significantly reduced.For instance,redundant pumps reduced the probability of ELU by 31.88%,while additional batteries decreased the occurrence of FTS by 36.45%.The results underscore the practical benefits of combining FTA and BN for enhancing system reliability,particularly in maritime applications where operational safety and efficiency are critical.This research provides valuable insights for maintenance planning and highlights the importance of redundancy in critical systems,especially as the industry transitions toward more autonomous vessels.展开更多
Cascading failures pose a serious threat to the survivability of underwater unmanned swarm networks(UUSNs),significantly limiting their service ability in collaborative missions such as military reconnaissance and env...Cascading failures pose a serious threat to the survivability of underwater unmanned swarm networks(UUSNs),significantly limiting their service ability in collaborative missions such as military reconnaissance and environmental monitoring.Existing failure models primarily focus on power grids and traffic systems,and don't address the unique challenges of weak-communication UUSNs.In UUSNs,cascading failure present a complex and dynamic process driven by the coupling of unstable acoustic channels,passive node drift,adversarial attacks,and network heterogeneity.To address these challenges,a directed weighted graph model of UUSNs is first developed,in which node positions are updated according to ocean-current-driven drift and link weights reflect the probability of successful acoustic transmission.Building on this UUSNs graph model,a cascading failure model is proposed that integrates a normal-failure-recovery state-cycle mechanism,multiple attack strategies,and routingbased load redistribution.Finally,under a five-level connectivity UUSNs scheme,simulations are conducted to analyze how dynamic topology,network load,node recovery delay,and attack modes jointly affect network survivability.The main findings are:(1)moderate node drift can improve survivability by activating weak links;(2)based-energy routing(BER)outperform based-depth routing(BDR)in harsh conditions;(3)node self-recovery time is critical to network survivability;(4)traditional degree-based critical node metrics are inadequate for weak-communication UUSNs.These results provide a theoretical foundation for designing robust survivability mechanisms in weak-communication UUSNs.展开更多
Objectives To identify core symptoms and symptom clusters in patients with neuromyelitis optica spectrum disorder(NMOSD)by network analysis.Methods From October 10 to 30,2023,140 patients with NMOSD were selected to p...Objectives To identify core symptoms and symptom clusters in patients with neuromyelitis optica spectrum disorder(NMOSD)by network analysis.Methods From October 10 to 30,2023,140 patients with NMOSD were selected to participate in this online questionnaire survey.The survey tools included a general information questionnaire and a self-made NMOSD symptoms scale,which included the prevalence,severity,and distress of 29 symptoms.Cluster analysis was used to identify symptom clusters,and network analysis was used to analyze the symptom network and node characteristics and central indicators including strength centrality(r_(s)),closeness centrality(r_(c))and betweeness centrality(r_(b))were used to identify core symptoms and symptom clusters.Results The most common symptom was pain(65.7%),followed by paraesthesia(65.0%),fatigue(65.0%),easy awakening(63.6%).Regarding the burden level of symptoms,pain was the most burdensome symptom,followed by paraesthesia,easy awakening,fatigue,and difficulty falling asleep.Six clusters were identified:somatosensory,motor,visual,and memory symptom clusters,bladder and rectum symptom clusters,sleep symptoms clusters,and neuropsychological symptom clusters.Fatigue(r_(s)=12.39,r_(b)=68.00,r_(c)=0.02)was the most central and prominent bridge symptom,and motor symptom cluster(r_(s)=2.68,r_(c)=0.10)was the most central symptom cluster among the six clusters.Conclusions Our study demonstrated the necessity of symptom management targeting fatigue,pain,and motor symptom cluster in patients with NMOSD.展开更多
The accurate mechanical analysis of thick-walled pressure vessel structures composed of advanced materials,such as hyperelastic and functionally graded materials(FGMs),is critical for ensuring their safety and optimiz...The accurate mechanical analysis of thick-walled pressure vessel structures composed of advanced materials,such as hyperelastic and functionally graded materials(FGMs),is critical for ensuring their safety and optimizing their design.However,conventional numerical methods can face challenges with the non-linearities inherent in hyperelasticity and the complex spatial variations in FGMs.This paper presents a novel hybrid numerical approach combining Physics-Informed Neural Networks(PINNs)with Finite Element Method(FEM)derived data for the robust analysis of thick-walled,axisymmetric,heterogeneous,hyperelastic pressure vessels with elliptical geometries.A PINN framework incorporating neo-Hookean constitutive relations is developed in MATLAB.To enhance training efficiency and accuracy,the PINN’s loss function is augmented with displacement data obtained from high-fidelity FEM simulations performed in ANSYS.The methodology is rigorously validated by comparing PINN-predicted displacement and von Mises stress fields against ANSYS benchmarks for various scenarios of FGMconfigurations(with material properties varying according to a power law)subjected to internal and external pressurization.The results demonstrate excellent agreement between the proposed hybrid PINN-FEMapproach and conventional FEMsolutions across all test cases,accurately capturing complex deformation patterns and stress concentrations.This study highlights the potential of data-augmented PINNs as an effective and accurate computational tool for tackling complex solid mechanics problems involving non-linearmaterials and significant heterogeneity,offering a promising avenue for future research in engineering design and analysis.展开更多
Objectives:SocialNetworkAddiction(SNA)is becoming increasingly prevalent among college students;however,there remains a lack of consensus regarding the measurement tools and their optimal cutoff score.This study aims ...Objectives:SocialNetworkAddiction(SNA)is becoming increasingly prevalent among college students;however,there remains a lack of consensus regarding the measurement tools and their optimal cutoff score.This study aims to validate the 21-item SocialNetwork Addiction Scale-Chinese(SNAS-C)in its Chinese version and to determine its optimal cutoff score for identifying potential SNA cases within the college student population.Methods:A crosssectional survey was conducted,recruiting 3387 college students.Latent profile analysis(LPA)and receiver operating characteristic(ROC)curve analysis were employed to establish the optimal cutoff score for the validated 21-item SNAS-C.Results:Three profile models were selected based on multiple statistical criteria,classifying participants into low-risk,moderate-risk,and high-risk groups.The highest-risk group was defined as“positive”for SNA,while the remaining groups were considered“negative”,serving as the reference standard for ROC analysis.The optimal cutoff score was determined to be 72(sensitivity:98.2%,specificity:96.86%),with an overall classification accuracy of 97.0%.The“positive”group reported significantly higher frequency of social network usage,greater digitalmedia dependence scores,and a higher incidence of network addiction.Conclusion:This study identified the optimal cutoff score for the SNAS-C as≥72,demonstrating high sensitivity,specificity,and diagnostic accuracy.This threshold effectively distinguishes between high-risk and low-risk SNA.展开更多
Aspect-oriented sentiment analysis is a meticulous sentiment analysis task that aims to analyse the sentiment polarity of specific aspects. Most of the current research builds graph convolutional networks based on dep...Aspect-oriented sentiment analysis is a meticulous sentiment analysis task that aims to analyse the sentiment polarity of specific aspects. Most of the current research builds graph convolutional networks based on dependent syntactic trees, which improves the classification performance of the models to some extent. However, the technical limitations of dependent syntactic trees can introduce considerable noise into the model. Meanwhile, it is difficult for a single graph convolutional network to aggregate both semantic and syntactic structural information of nodes, which affects the final sentence classification. To cope with the above problems, this paper proposes a bi-channel graph convolutional network model. The model introduces a phrase structure tree and transforms it into a hierarchical phrase matrix. The adjacency matrix of the dependent syntactic tree and the hierarchical phrase matrix are combined as the initial matrix of the graph convolutional network to enhance the syntactic information. The semantic information feature representations of the sentences are obtained by the graph convolutional network with a multi-head attention mechanism and fused to achieve complementary learning of dual-channel features. Experimental results show that the model performs well and improves the accuracy of sentiment classification on three public benchmark datasets, namely Rest14, Lap14 and Twitter.展开更多
The construction of“park cities”requires a systematic thinking to coordinate the networked development of park system and break through the limitation of emphasizing scale and grade and neglecting dynamic correlatio...The construction of“park cities”requires a systematic thinking to coordinate the networked development of park system and break through the limitation of emphasizing scale and grade and neglecting dynamic correlation in traditional planning.Taking Haidian District of Beijing as an example,the social network analysis method is introduced to construct the network model of park green spaces.Through indicators such as clustering coefficient,network density and node centrality,the characteristics of its spatial structure and hierarchical relationship are analyzed.It is found that the network integrity presents the characteristics of“highly local concentration and global fragmentation”,fragmented park green space network and missing spatial connection,isolated clusters and collaborative failure,as well as the spatial mismatch between population and resource supply and demand.Hierarchical issues include“structural imbalance and functional disorder”,disorder between network hierarchy and park level,misalignment of functional hierarchy leading to weakened network risk resistance capacity,and a relatively dense distribution of core nodes,etc.In response to the above problems,a multi-level spatial intervention strategy should be adopted to solve the overall problem of the network.Meanwhile,it is needed to clarify the positioning of a park itself and improve the hierarchical system,so as to construct a multi-level and multi-scale park green space network,contribute to the construction of a park city,and provide residents with more diverse activity venues.展开更多
Dear Editor,We read with a great interest the recently published systematic review by Shamsikhani and Hosseini titled,“Foot reflexology on nausea and vomiting:A systematic review.”[1]While the authors provided a com...Dear Editor,We read with a great interest the recently published systematic review by Shamsikhani and Hosseini titled,“Foot reflexology on nausea and vomiting:A systematic review.”[1]While the authors provided a comprehensive qualitative synthesis of six studies meeting their inclusion criteria,we believe that additional quantitative analysis would strengthen the evidence base for foot reflexology in managing nausea and vomiting.We conducted a complementary meta-analysis to provide quantitative evidence supporting the qualitative findings presented in the systematic review.展开更多
Traditional Chinese medicine(TCM)has played a significant role in the prevention and treatment of chronic heart failure(CHF).To study TCM diagnosis of CHF,a total of 278 Chinese clinical research articles on the study...Traditional Chinese medicine(TCM)has played a significant role in the prevention and treatment of chronic heart failure(CHF).To study TCM diagnosis of CHF,a total of 278 Chinese clinical research articles on the study of CHF syndromes in recent 40 years retrieved from Web of Science,Scopus,Pub Med,Embase,CNKI,Wanfang Data,Cq VIP,and Sino Med.According to cumulative frequency analysis,network analysis,and hierarchical cluster analysis,the study found the distribution of CHF syndromes was syndrome of qi deficiency with blood stasis,syndrome of qi and yin deficiency,syndrome of yang deficiency with water flooding,syndrome of heart blood stasis obstruction,syndrome of turbid phlegm,and syndrome of collapse due to primordial yang deficiency.The syndrome elements on location of illness were heart,kidney,lung,and spleen.The syndrome elements on nature of illness were qi deficiency,blood stasis,yang deficiency,yin deficiency,water retention,and turbid phlegm.These findings can provide reference to the research on diagnosis and treatment of CHF,and contribute to the study on syndrome standardization and objective research of TCM diagnosis.展开更多
To the editor:“A recent systematic review shows that the risk of death by suicide is 100 times higher in people living with HIV than in the general population”—World Health Organization,2022 The estimate that the r...To the editor:“A recent systematic review shows that the risk of death by suicide is 100 times higher in people living with HIV than in the general population”—World Health Organization,2022 The estimate that the risk of suicide is 100-fold higher in people with HIV(PWH)than in the general population is widely cited,including in the World Health Organization’s(WHO’s)World Mental Health report from which the above quote is taken.1 This figure originates from a systematic review and meta-analysis by Pelton and colleagues,who estimated the‘lifetime incidence’of suicide among PWH2 and directly compared this measure to the WHO’s annual global suicide mortality rate.展开更多
Cryptocurrency has gained popularity as a potential new global payment method.It has the potential to be faster,cheaper,and more secure than existing payment networks,making it a game-changer in the global economy.How...Cryptocurrency has gained popularity as a potential new global payment method.It has the potential to be faster,cheaper,and more secure than existing payment networks,making it a game-changer in the global economy.However,more research is needed to identify the factors driving cryptocurrency adoption and understand its impact.We use social network analysis(SNA)to identify the influencing factors and reveal the impact of each on cryptocurrency adoption.Our analysis initially revealed 44 influential factors,which were later reduced to 25 factors,each exerting a different influence.Based on the SNA,we classify these factors into highly,moderately,and least influential categories.Discomfort and optimism are the most influential determinants of adoption.Moderately influential factors include trust,risk,relative advantage,social influence,and perceived behavioral control.Price/value,facilitating conditions,compatibility,and usefulness are the least influential.The factors affecting cryptocurrency adoption are interdependent.Our findings can help policymakers understand the factors influencing cryptocurrency adoption and aid in developing appropriate legal frameworks for cryptocurrency use.展开更多
Objectives:This study aimed to assess the reliability and validity of the abbreviated Committed Action Questionnaire(CAQ-8)in a cohort of 1635 Chinese university students.Methods:Participants completed the Chinese ver...Objectives:This study aimed to assess the reliability and validity of the abbreviated Committed Action Questionnaire(CAQ-8)in a cohort of 1635 Chinese university students.Methods:Participants completed the Chinese version of the CAQ-8 along with other standardized measures,including the Acceptance and Action Questionnaire-II(AAQ-II),the Valuing Questionnaire(VQ),the Satisfaction with Life Scale(SWLS),the Depression Anxiety Stress Scales(DASS-21),and the World Health Organization Fiveitem Well-Being Index(WHO-5).A retest was conducted one month later with 300 valid responses.Results:Exploratory factor analysis(n=818)identified a 2-factor structure,confirmed through validated factor analysis(n=817),showing good fit indices(CFI=0.990,RMSEA=0.040).Measurement equivalence across genders was established.The CAQ-8 showed significant positive correlations with life satisfaction,mental health,and values,and negative correlations with depression,anxiety,stress,and experiential avoidance.The scale demonstrated good internal consistency(Cronbach’sα=0.76)and retest reliability(ICC=0.70).Network analysis confirmed the robustness of the 2-factor model,with item 4 in CAQ-8 identified as a core item.Conclusion:The CAQ-8 is a reliable and valid tool for measuring committed action within the psychological flexibility model in Chinese populations.展开更多
Objective To identify core acupoint patterns and elucidate the molecular mechanisms of acupuncture for primary depressive disorder(PDD)through data mining and network analysis.Methods A comprehensive literature search...Objective To identify core acupoint patterns and elucidate the molecular mechanisms of acupuncture for primary depressive disorder(PDD)through data mining and network analysis.Methods A comprehensive literature search was conducted across PubMed,Embase,Ovid Technologies(OVID),Web of Science,Cochrane Library,China National Knowledge Infrastructure(CNKI),China National Knowledge Infrastructure Database(VIP),Wanfang Data,and SinoMed Database from database foundation to January 31,2025,for clinical studies on acupuncture treatment of PDD.Descriptive statistics,high-frequency acupoint analysis,degree and betweenness centrality evaluation,and core acupoint prescription mining identified predominant therapeutic combinations for PDD.Network acupuncture was used to predict therapeutic target for the core acupoint prescription.Subsequent protein-protein interaction(PPI)network and molecular complex detection(MCODE)analyses were conducted to identify the key targets and functional modules.Gene Ontology(GO)and Kyoto Encyclopedia of Genes and Genomes(KEGG)analyses explored the underlying biological mechanisms of the core acupoint prescription in treating PDD.Results A total of 57 acupoint prescriptions underwent systematic analysis.The core therapeutic combinations comprised Baihui(GV20),Yintang(GV29),Neiguan(PC6),Hegu(LI4),and Shenmen(HT7).Network acupuncture analysis identified 88 potential therapeutic targets(79 overlapping with PDD),while PPI network analysis revealed central regulatory nodes,including interleukin(IL)-6,IL-1β,tumor necrosis factor(TNF)-α,toll-like receptor 4(TLR4),IL-10,brain-derived neurotrophic factor(BDNF),transforming growth factor(TGF)-β1,C-XC motif chemokine ligand 10(CXCL10),mitogen-activated protein kinase 3(MAPK3),and nitric oxide synthase 1(NOS1).MCODE-based modular analysis further elucidated three functionally coherent clusters:inflammation-homeostasis(score=6.571),plasticity-neurotransmission(score=3.143),and oxidative stress(score=3.000).GO and KEGG analyses demonstrated significant enrichment of the MAPK,phosphoinositide 3-kinase/protein kinase B(PI3K/Akt),and hypoxia-inducible factor(HIF)-1 signaling pathways.These mechanistic insights suggested that the antidepressant effects mediated through mechanisms of neuroinflammatory regulation,neuroplasticity restoration,and immune-oxidative stress homeostasis.Conclusion This study reveals that acupuncture alleviates depression through a multi-level mechanism,primarily involving the neuroinflammation suppression,neuroplasticity enhancement,and oxidative stress regulation.These findings systematically clarify the underlying mechanisms of acupuncture’s antidepressant effects and identify novel therapeutic targets for further mechanistic research.展开更多
We highly commend Dr Souza et al.1for their systematic review research.The authors conducted a detailed investigation into the effects of ischemic preconditioning(IPC)on athletic performance,comparing it with placebo ...We highly commend Dr Souza et al.1for their systematic review research.The authors conducted a detailed investigation into the effects of ischemic preconditioning(IPC)on athletic performance,comparing it with placebo and no-intervention conditions.The study found that while IPC demonstrated superior effects over the no-intervention group in certain metrics(e.g.,time to exhaustion),its performance did not significantly surpass that of the placebo group.This suggests that the potential benefits of IPC may partially stem from participants’psychological expectations,or placebo effects.The study also highlighted the significant impact of placebo interventions on athletic performance,emphasizing the importance of distinguishing between placebo and no-intervention conditions in experimental designs.展开更多
Frequent extreme heat events around the world not only pose a major threat to human health but also cause significant economic losses to the livestock industry.The existing management practices are insufficient to ful...Frequent extreme heat events around the world not only pose a major threat to human health but also cause significant economic losses to the livestock industry.The existing management practices are insufficient to fully prevent heat stress with an urgent need to develop preventive medicines.The aim of this study was to develop an antiheat stress Chinese herbal formula(CHF)via big data analysis techniques and to evaluate its anti-heat stress effect and mechanism of action via pharmacodynamic evaluation and network pharmacology analysis.Many anti-heat stress CHFs were collected from the Chinese National Knowledge Infrastructure(CNKI)database.Three alternative CHFs were obtained via unsupervised entropy hierarchical clustering analysis,and the most effective CHF against heat stress,Shidi Jieshu decoction(SJD),was obtained by screening in a mouse heat stress model.In dry and hot environments,SJD significantly improved the heat tolerance of AA broilers by 4-6℃.In a humid and hot environment,pretreatment with 2%SJD resulted in 100%survival of Wenchang chickens at high temperatures.The main active ingredients of SJD were identified as muntjacoside E,timosaponin C,macrostemonoside H and mangiferin via ultraperformance liquid chromatography/mass spectrometry(UPLC/MS)and database comparison.The active ingredients of SJD were found to target tumor necrosis factor-α(TNF-α),signal transducer activator of transcription 3(STAT3)and epidermal growth factor receptor(EGFR).Finally,the safety of the new formulation was assessed in an acute oral toxicity study in rats.The SJDs developed in this study provide a new option for the prevention of heat stress in animal husbandry and offer new insights for further research on anti-heat stress.展开更多
BACKGROUND Upper gastrointestinal cancer(UGIC),including esophageal and gastric cancers,poses a major global health challenge due to its high morbidity and mortality.During the preoperative period,patients often face ...BACKGROUND Upper gastrointestinal cancer(UGIC),including esophageal and gastric cancers,poses a major global health challenge due to its high morbidity and mortality.During the preoperative period,patients often face functional decline,malnutrition,and psychological stress,which can impair recovery.Prehabilitation,a multidisciplinary preoperative intervention,shows promise in optimizing patients'physical and mental status.AIM To evaluate the impact of prehabilitation on patients undergoing UGIC surgery and provide a basis for implementation of the prehabilitation compound plan.METHODS A computerized search of databases including Web of Science,PubMed,EMBASE,The Cochrane Library,Cumulative Index to Nursing and Allied Health Literature,China National Knowledge Infrastructure,Wanfang,and Chinese Science and Technology Journal Database was used to collect clinical trials on the impact of prehabilitation on patients undergoing UGIC surgery.After screening,a meta-analysis was conducted using Review Manager 5.0 software,and linear regression analysis was performed on the prehabilitation duration and outcome indicators.RESULTS A total of 13 clinical trials were ultimately included,with 8 literature quality evaluations at A level and 5 literature quality evaluations at B level.The meta-analysis results showed that compared with conventional nursing,the prehabilitation group had higher six-minute walk distance,lower postoperative complications and mortality rates,and shorter hospital stays,with statistically significant differences;there were no statistically significant differences in intensive care unit monitoring time and albumin levels between the two groups;regression analysis between prehabilitation duration and outcome indicators showed no significant relationship.CONCLUSION Prehabilitation can improve the perioperative functional ability of patients with UGIC and promote postoperative recovery,but its impact on nutrition,psychology,and quality of life needs to be further explored through more high-quality trials;in addition,further research is needed on the prehabilitation time,location,and specific plan.展开更多
文摘The increasing electrification of urban transportation,i.e.,subways and electric vehicles(EV),brings more interactions between the power system and transportation system and further results in fault propagation across them.To analyze vulnerability of the coupling system under extreme events,this paper establishes a multi-layer urban electric-transportation interdependent network(ETIN)model.First,a weighted coupled metro-road traffic network(CTN)model and network path planning approach are proposed.A prospect theory-based failure load redistribution(FLR)method is further established to account for uncertainty of TN link capacity affected by power supply.Second,topology and emergency control strategy of power network(PN)are modeled,followed by formulation of multi-layer ETIN model.In particular,the inter-layer fault propagation from PN to TN is modeled based on power supply correlation strength,while from TN to PN is modeled based on traffic flow.A few indexes are then defined to quantify vulnerability of ETIN under deliberate attack.Finally,the proposed method is verified on an electric-transportation system to show influence of fault propagations within ETIN on its vulnerability under extreme events.
基金support from the National Natural Science Foundation of China(Grant No.22275018).
文摘The combustion and detonation processes of energetic materials exhibit remarkable complexity and ultra-fast transient characteristics.While reactive molecular dynamics has been extensively employed to investigate the reaction dynamics of energetic materials,its utility is often constrained to capturing only fundamental reaction events and species information,thereby limiting mechanistic investigations of complex reaction pathways.To elucidate the topological features of energetic material reaction networks and identify critical reaction pathways with high fidelity,this study presents ReacNetwork-an advanced large-scale reaction network analysis methodology that synergistically integrates complex network theory with molecular simulation techniques.Specifically,we have developed a multi-dimensional feature screening protocol based on node centrality metrics and K-shell decomposition algorithms.Takingα-Hexahydro-1,3,5-trinitro-1,3,5-triazine(α-RDX)as the subject,we successfully constructed a comprehensive high-temperature thermal decomposition reaction network consisting of 1,134 distinct chemical species and 3,626 elementary reactions.Through systematic application of community detection algorithms and global topological feature extraction techniques,we achieved effective dimensionality reduction and successfully identified the dominant reaction pathway within theα-RDX thermal decomposition network.The computational results not only validate the well-established initial reaction mechanism dominated by N-NO2 homolytic bond cleavage,but also provide unprecedented visualization ofα-RDX framework ring-opening dynamics and subsequent radical chain propagation networks.
基金supported by the Anhui Philosophical and Social Science Fund for University Research:The Application of Painting Psychological Analysis in College Students’Mental Health Education Courses(Grant#:2023AH052874),which has provided essential financial support for data collection.
文摘This study explores the core characteristics,dynamic progression of the depression-anxiety-stress network among Chinese higher vocational college freshmen and its association with life satisfaction,and identifies key nodes and critical intervention points.Participants were 295 higher vocational college freshmen(male=137;M=18.52,SD=0.69)completing two follow-up surveys(5-month interval).Measures included depression-anxiety-stress symptoms and life satisfaction,analyzed via cross-sectional and binary cross-lagged panel network analysis.The results showed that“Easily agitated”was the central node(strength=1.519,EI=1.967);“Irritable”and“Mouth Dryness”were top predictors(Out-EI=1.101,1.100),with depressive symptoms as the convergence hub.“Easily agitated”had the strongest direct negative impact on life satisfaction(cross-cluster out-predictability=−0.653).This study elucidates depression-anxietystress network mechanisms in higher vocational freshmen,providing a theoretical framework and targeted intervention guidance(e.g.,focusing on somatic and emotional nodes).
文摘Background:Amid the global rise in adolescent sedentary behavior and psychological distress,extant research has largely focused on variable-level associations,neglecting symptom-level interactions.This study applies network analysis,aims to delineate the interconnections among sedentary time,social support,social exclusion,and psychological distress in Chinese students,and to identify core and bridge symptoms to inform targeted interventions.Methods:This study employed a cross-sectional design to investigate the complex relationships among sedentary behavior,social support,social exclusion,and psychological distress among Chinese students.The research involved 459 high school and university students,using network analysis and mediation models to examine these relationships.Results:Network analysis revealed that the network had a density of 58.33%and an average edge weight of 0.11.In terms of centrality,stress had the highest expected influence(EI=1.135),acting as the core amplifier in the network.Sedentary behavior demonstrated the highest bridging expected influence,functioning as a critical bridge for cross-community transmission.Conversely,friend support showed the lowest bridging EI with a negative value,indicating its effectiveness in blocking cross-community diffusion and alleviating symptoms.Conclusion:With stress acting as the most influential“core engine”within the symptom network and sedentary behavior serving as the key“bridge”for cross-community transmission,interventions should first target stress to weaken the overall symptom cascade,followed by reducing sedentary behavior or enhancing friend support to disrupt cross-community pathways,thereby achieving a core-bridge dual blockade.
基金supported by Istanbul Technical University(Project No.45698)supported through the“Young Researchers’Career Development Project-training of doctoral students”of the Croatian Science Foundation.
文摘This paper investigates the reliability of internal marine combustion engines using an integrated approach that combines Fault Tree Analysis(FTA)and Bayesian Networks(BN).FTA provides a structured,top-down method for identifying critical failure modes and their root causes,while BN introduces flexibility in probabilistic reasoning,enabling dynamic updates based on new evidence.This dual methodology overcomes the limitations of static FTA models,offering a comprehensive framework for system reliability analysis.Critical failures,including External Leakage(ELU),Failure to Start(FTS),and Overheating(OHE),were identified as key risks.By incorporating redundancy into high-risk components such as pumps and batteries,the likelihood of these failures was significantly reduced.For instance,redundant pumps reduced the probability of ELU by 31.88%,while additional batteries decreased the occurrence of FTS by 36.45%.The results underscore the practical benefits of combining FTA and BN for enhancing system reliability,particularly in maritime applications where operational safety and efficiency are critical.This research provides valuable insights for maintenance planning and highlights the importance of redundancy in critical systems,especially as the industry transitions toward more autonomous vessels.
基金supported in part by the National Natural Science Foundation of China(Key Program)under Grant No.62031021。
文摘Cascading failures pose a serious threat to the survivability of underwater unmanned swarm networks(UUSNs),significantly limiting their service ability in collaborative missions such as military reconnaissance and environmental monitoring.Existing failure models primarily focus on power grids and traffic systems,and don't address the unique challenges of weak-communication UUSNs.In UUSNs,cascading failure present a complex and dynamic process driven by the coupling of unstable acoustic channels,passive node drift,adversarial attacks,and network heterogeneity.To address these challenges,a directed weighted graph model of UUSNs is first developed,in which node positions are updated according to ocean-current-driven drift and link weights reflect the probability of successful acoustic transmission.Building on this UUSNs graph model,a cascading failure model is proposed that integrates a normal-failure-recovery state-cycle mechanism,multiple attack strategies,and routingbased load redistribution.Finally,under a five-level connectivity UUSNs scheme,simulations are conducted to analyze how dynamic topology,network load,node recovery delay,and attack modes jointly affect network survivability.The main findings are:(1)moderate node drift can improve survivability by activating weak links;(2)based-energy routing(BER)outperform based-depth routing(BDR)in harsh conditions;(3)node self-recovery time is critical to network survivability;(4)traditional degree-based critical node metrics are inadequate for weak-communication UUSNs.These results provide a theoretical foundation for designing robust survivability mechanisms in weak-communication UUSNs.
基金supported by the Specific Research Fund for Top-notch Talents of Guangdong Provincial Hospital of Chinese Medicine(No.2022KT1188).
文摘Objectives To identify core symptoms and symptom clusters in patients with neuromyelitis optica spectrum disorder(NMOSD)by network analysis.Methods From October 10 to 30,2023,140 patients with NMOSD were selected to participate in this online questionnaire survey.The survey tools included a general information questionnaire and a self-made NMOSD symptoms scale,which included the prevalence,severity,and distress of 29 symptoms.Cluster analysis was used to identify symptom clusters,and network analysis was used to analyze the symptom network and node characteristics and central indicators including strength centrality(r_(s)),closeness centrality(r_(c))and betweeness centrality(r_(b))were used to identify core symptoms and symptom clusters.Results The most common symptom was pain(65.7%),followed by paraesthesia(65.0%),fatigue(65.0%),easy awakening(63.6%).Regarding the burden level of symptoms,pain was the most burdensome symptom,followed by paraesthesia,easy awakening,fatigue,and difficulty falling asleep.Six clusters were identified:somatosensory,motor,visual,and memory symptom clusters,bladder and rectum symptom clusters,sleep symptoms clusters,and neuropsychological symptom clusters.Fatigue(r_(s)=12.39,r_(b)=68.00,r_(c)=0.02)was the most central and prominent bridge symptom,and motor symptom cluster(r_(s)=2.68,r_(c)=0.10)was the most central symptom cluster among the six clusters.Conclusions Our study demonstrated the necessity of symptom management targeting fatigue,pain,and motor symptom cluster in patients with NMOSD.
文摘The accurate mechanical analysis of thick-walled pressure vessel structures composed of advanced materials,such as hyperelastic and functionally graded materials(FGMs),is critical for ensuring their safety and optimizing their design.However,conventional numerical methods can face challenges with the non-linearities inherent in hyperelasticity and the complex spatial variations in FGMs.This paper presents a novel hybrid numerical approach combining Physics-Informed Neural Networks(PINNs)with Finite Element Method(FEM)derived data for the robust analysis of thick-walled,axisymmetric,heterogeneous,hyperelastic pressure vessels with elliptical geometries.A PINN framework incorporating neo-Hookean constitutive relations is developed in MATLAB.To enhance training efficiency and accuracy,the PINN’s loss function is augmented with displacement data obtained from high-fidelity FEM simulations performed in ANSYS.The methodology is rigorously validated by comparing PINN-predicted displacement and von Mises stress fields against ANSYS benchmarks for various scenarios of FGMconfigurations(with material properties varying according to a power law)subjected to internal and external pressurization.The results demonstrate excellent agreement between the proposed hybrid PINN-FEMapproach and conventional FEMsolutions across all test cases,accurately capturing complex deformation patterns and stress concentrations.This study highlights the potential of data-augmented PINNs as an effective and accurate computational tool for tackling complex solid mechanics problems involving non-linearmaterials and significant heterogeneity,offering a promising avenue for future research in engineering design and analysis.
基金supported by the National Natural Science Foundation of China(Grant No.72364006).
文摘Objectives:SocialNetworkAddiction(SNA)is becoming increasingly prevalent among college students;however,there remains a lack of consensus regarding the measurement tools and their optimal cutoff score.This study aims to validate the 21-item SocialNetwork Addiction Scale-Chinese(SNAS-C)in its Chinese version and to determine its optimal cutoff score for identifying potential SNA cases within the college student population.Methods:A crosssectional survey was conducted,recruiting 3387 college students.Latent profile analysis(LPA)and receiver operating characteristic(ROC)curve analysis were employed to establish the optimal cutoff score for the validated 21-item SNAS-C.Results:Three profile models were selected based on multiple statistical criteria,classifying participants into low-risk,moderate-risk,and high-risk groups.The highest-risk group was defined as“positive”for SNA,while the remaining groups were considered“negative”,serving as the reference standard for ROC analysis.The optimal cutoff score was determined to be 72(sensitivity:98.2%,specificity:96.86%),with an overall classification accuracy of 97.0%.The“positive”group reported significantly higher frequency of social network usage,greater digitalmedia dependence scores,and a higher incidence of network addiction.Conclusion:This study identified the optimal cutoff score for the SNAS-C as≥72,demonstrating high sensitivity,specificity,and diagnostic accuracy.This threshold effectively distinguishes between high-risk and low-risk SNA.
文摘Aspect-oriented sentiment analysis is a meticulous sentiment analysis task that aims to analyse the sentiment polarity of specific aspects. Most of the current research builds graph convolutional networks based on dependent syntactic trees, which improves the classification performance of the models to some extent. However, the technical limitations of dependent syntactic trees can introduce considerable noise into the model. Meanwhile, it is difficult for a single graph convolutional network to aggregate both semantic and syntactic structural information of nodes, which affects the final sentence classification. To cope with the above problems, this paper proposes a bi-channel graph convolutional network model. The model introduces a phrase structure tree and transforms it into a hierarchical phrase matrix. The adjacency matrix of the dependent syntactic tree and the hierarchical phrase matrix are combined as the initial matrix of the graph convolutional network to enhance the syntactic information. The semantic information feature representations of the sentences are obtained by the graph convolutional network with a multi-head attention mechanism and fused to achieve complementary learning of dual-channel features. Experimental results show that the model performs well and improves the accuracy of sentiment classification on three public benchmark datasets, namely Rest14, Lap14 and Twitter.
文摘The construction of“park cities”requires a systematic thinking to coordinate the networked development of park system and break through the limitation of emphasizing scale and grade and neglecting dynamic correlation in traditional planning.Taking Haidian District of Beijing as an example,the social network analysis method is introduced to construct the network model of park green spaces.Through indicators such as clustering coefficient,network density and node centrality,the characteristics of its spatial structure and hierarchical relationship are analyzed.It is found that the network integrity presents the characteristics of“highly local concentration and global fragmentation”,fragmented park green space network and missing spatial connection,isolated clusters and collaborative failure,as well as the spatial mismatch between population and resource supply and demand.Hierarchical issues include“structural imbalance and functional disorder”,disorder between network hierarchy and park level,misalignment of functional hierarchy leading to weakened network risk resistance capacity,and a relatively dense distribution of core nodes,etc.In response to the above problems,a multi-level spatial intervention strategy should be adopted to solve the overall problem of the network.Meanwhile,it is needed to clarify the positioning of a park itself and improve the hierarchical system,so as to construct a multi-level and multi-scale park green space network,contribute to the construction of a park city,and provide residents with more diverse activity venues.
文摘Dear Editor,We read with a great interest the recently published systematic review by Shamsikhani and Hosseini titled,“Foot reflexology on nausea and vomiting:A systematic review.”[1]While the authors provided a comprehensive qualitative synthesis of six studies meeting their inclusion criteria,we believe that additional quantitative analysis would strengthen the evidence base for foot reflexology in managing nausea and vomiting.We conducted a complementary meta-analysis to provide quantitative evidence supporting the qualitative findings presented in the systematic review.
基金financed by the grants from the National Natural Science Foundation of China(No.81803996)Shanghai Key Laboratory of Health Identification and Assessment(No.21DZ2271000)。
文摘Traditional Chinese medicine(TCM)has played a significant role in the prevention and treatment of chronic heart failure(CHF).To study TCM diagnosis of CHF,a total of 278 Chinese clinical research articles on the study of CHF syndromes in recent 40 years retrieved from Web of Science,Scopus,Pub Med,Embase,CNKI,Wanfang Data,Cq VIP,and Sino Med.According to cumulative frequency analysis,network analysis,and hierarchical cluster analysis,the study found the distribution of CHF syndromes was syndrome of qi deficiency with blood stasis,syndrome of qi and yin deficiency,syndrome of yang deficiency with water flooding,syndrome of heart blood stasis obstruction,syndrome of turbid phlegm,and syndrome of collapse due to primordial yang deficiency.The syndrome elements on location of illness were heart,kidney,lung,and spleen.The syndrome elements on nature of illness were qi deficiency,blood stasis,yang deficiency,yin deficiency,water retention,and turbid phlegm.These findings can provide reference to the research on diagnosis and treatment of CHF,and contribute to the study on syndrome standardization and objective research of TCM diagnosis.
基金supported by the Swiss National Science Foundation(grant numbers 193381 and 189498)the US National Institutes of Health(the National Institute of Allergy and Infectious Diseases,the Eunice Kennedy Shriver National Institute of Child Health and Human Development,the National Cancer Institute,the National Institute of Mental Health,the National Institute on Drug Abuse,the National Heart,Lung,and Blood Institute,the National Institute on Alcohol Abuse and Alcoholism,the National Institute of Diabetes and Digestive and Kidney Diseases and the Fogarty International Center)(grant numbers U01AI069924 and 1K43TW012840-01).
文摘To the editor:“A recent systematic review shows that the risk of death by suicide is 100 times higher in people living with HIV than in the general population”—World Health Organization,2022 The estimate that the risk of suicide is 100-fold higher in people with HIV(PWH)than in the general population is widely cited,including in the World Health Organization’s(WHO’s)World Mental Health report from which the above quote is taken.1 This figure originates from a systematic review and meta-analysis by Pelton and colleagues,who estimated the‘lifetime incidence’of suicide among PWH2 and directly compared this measure to the WHO’s annual global suicide mortality rate.
文摘Cryptocurrency has gained popularity as a potential new global payment method.It has the potential to be faster,cheaper,and more secure than existing payment networks,making it a game-changer in the global economy.However,more research is needed to identify the factors driving cryptocurrency adoption and understand its impact.We use social network analysis(SNA)to identify the influencing factors and reveal the impact of each on cryptocurrency adoption.Our analysis initially revealed 44 influential factors,which were later reduced to 25 factors,each exerting a different influence.Based on the SNA,we classify these factors into highly,moderately,and least influential categories.Discomfort and optimism are the most influential determinants of adoption.Moderately influential factors include trust,risk,relative advantage,social influence,and perceived behavioral control.Price/value,facilitating conditions,compatibility,and usefulness are the least influential.The factors affecting cryptocurrency adoption are interdependent.Our findings can help policymakers understand the factors influencing cryptocurrency adoption and aid in developing appropriate legal frameworks for cryptocurrency use.
文摘Objectives:This study aimed to assess the reliability and validity of the abbreviated Committed Action Questionnaire(CAQ-8)in a cohort of 1635 Chinese university students.Methods:Participants completed the Chinese version of the CAQ-8 along with other standardized measures,including the Acceptance and Action Questionnaire-II(AAQ-II),the Valuing Questionnaire(VQ),the Satisfaction with Life Scale(SWLS),the Depression Anxiety Stress Scales(DASS-21),and the World Health Organization Fiveitem Well-Being Index(WHO-5).A retest was conducted one month later with 300 valid responses.Results:Exploratory factor analysis(n=818)identified a 2-factor structure,confirmed through validated factor analysis(n=817),showing good fit indices(CFI=0.990,RMSEA=0.040).Measurement equivalence across genders was established.The CAQ-8 showed significant positive correlations with life satisfaction,mental health,and values,and negative correlations with depression,anxiety,stress,and experiential avoidance.The scale demonstrated good internal consistency(Cronbach’sα=0.76)and retest reliability(ICC=0.70).Network analysis confirmed the robustness of the 2-factor model,with item 4 in CAQ-8 identified as a core item.Conclusion:The CAQ-8 is a reliable and valid tool for measuring committed action within the psychological flexibility model in Chinese populations.
文摘Objective To identify core acupoint patterns and elucidate the molecular mechanisms of acupuncture for primary depressive disorder(PDD)through data mining and network analysis.Methods A comprehensive literature search was conducted across PubMed,Embase,Ovid Technologies(OVID),Web of Science,Cochrane Library,China National Knowledge Infrastructure(CNKI),China National Knowledge Infrastructure Database(VIP),Wanfang Data,and SinoMed Database from database foundation to January 31,2025,for clinical studies on acupuncture treatment of PDD.Descriptive statistics,high-frequency acupoint analysis,degree and betweenness centrality evaluation,and core acupoint prescription mining identified predominant therapeutic combinations for PDD.Network acupuncture was used to predict therapeutic target for the core acupoint prescription.Subsequent protein-protein interaction(PPI)network and molecular complex detection(MCODE)analyses were conducted to identify the key targets and functional modules.Gene Ontology(GO)and Kyoto Encyclopedia of Genes and Genomes(KEGG)analyses explored the underlying biological mechanisms of the core acupoint prescription in treating PDD.Results A total of 57 acupoint prescriptions underwent systematic analysis.The core therapeutic combinations comprised Baihui(GV20),Yintang(GV29),Neiguan(PC6),Hegu(LI4),and Shenmen(HT7).Network acupuncture analysis identified 88 potential therapeutic targets(79 overlapping with PDD),while PPI network analysis revealed central regulatory nodes,including interleukin(IL)-6,IL-1β,tumor necrosis factor(TNF)-α,toll-like receptor 4(TLR4),IL-10,brain-derived neurotrophic factor(BDNF),transforming growth factor(TGF)-β1,C-XC motif chemokine ligand 10(CXCL10),mitogen-activated protein kinase 3(MAPK3),and nitric oxide synthase 1(NOS1).MCODE-based modular analysis further elucidated three functionally coherent clusters:inflammation-homeostasis(score=6.571),plasticity-neurotransmission(score=3.143),and oxidative stress(score=3.000).GO and KEGG analyses demonstrated significant enrichment of the MAPK,phosphoinositide 3-kinase/protein kinase B(PI3K/Akt),and hypoxia-inducible factor(HIF)-1 signaling pathways.These mechanistic insights suggested that the antidepressant effects mediated through mechanisms of neuroinflammatory regulation,neuroplasticity restoration,and immune-oxidative stress homeostasis.Conclusion This study reveals that acupuncture alleviates depression through a multi-level mechanism,primarily involving the neuroinflammation suppression,neuroplasticity enhancement,and oxidative stress regulation.These findings systematically clarify the underlying mechanisms of acupuncture’s antidepressant effects and identify novel therapeutic targets for further mechanistic research.
文摘We highly commend Dr Souza et al.1for their systematic review research.The authors conducted a detailed investigation into the effects of ischemic preconditioning(IPC)on athletic performance,comparing it with placebo and no-intervention conditions.The study found that while IPC demonstrated superior effects over the no-intervention group in certain metrics(e.g.,time to exhaustion),its performance did not significantly surpass that of the placebo group.This suggests that the potential benefits of IPC may partially stem from participants’psychological expectations,or placebo effects.The study also highlighted the significant impact of placebo interventions on athletic performance,emphasizing the importance of distinguishing between placebo and no-intervention conditions in experimental designs.
基金supported by the Major Special Science and Technology Plan(202302AA310020)the National Natural Science Foundation of China(NSFC)(32072925,32473087)the National Student Innovation and Entrepreneurship Training Program of Huazhong Agricultural University(202310504018)。
文摘Frequent extreme heat events around the world not only pose a major threat to human health but also cause significant economic losses to the livestock industry.The existing management practices are insufficient to fully prevent heat stress with an urgent need to develop preventive medicines.The aim of this study was to develop an antiheat stress Chinese herbal formula(CHF)via big data analysis techniques and to evaluate its anti-heat stress effect and mechanism of action via pharmacodynamic evaluation and network pharmacology analysis.Many anti-heat stress CHFs were collected from the Chinese National Knowledge Infrastructure(CNKI)database.Three alternative CHFs were obtained via unsupervised entropy hierarchical clustering analysis,and the most effective CHF against heat stress,Shidi Jieshu decoction(SJD),was obtained by screening in a mouse heat stress model.In dry and hot environments,SJD significantly improved the heat tolerance of AA broilers by 4-6℃.In a humid and hot environment,pretreatment with 2%SJD resulted in 100%survival of Wenchang chickens at high temperatures.The main active ingredients of SJD were identified as muntjacoside E,timosaponin C,macrostemonoside H and mangiferin via ultraperformance liquid chromatography/mass spectrometry(UPLC/MS)and database comparison.The active ingredients of SJD were found to target tumor necrosis factor-α(TNF-α),signal transducer activator of transcription 3(STAT3)and epidermal growth factor receptor(EGFR).Finally,the safety of the new formulation was assessed in an acute oral toxicity study in rats.The SJDs developed in this study provide a new option for the prevention of heat stress in animal husbandry and offer new insights for further research on anti-heat stress.
基金Supported by Key Project of Jiangsu Provincial Health(ZD2022052).
文摘BACKGROUND Upper gastrointestinal cancer(UGIC),including esophageal and gastric cancers,poses a major global health challenge due to its high morbidity and mortality.During the preoperative period,patients often face functional decline,malnutrition,and psychological stress,which can impair recovery.Prehabilitation,a multidisciplinary preoperative intervention,shows promise in optimizing patients'physical and mental status.AIM To evaluate the impact of prehabilitation on patients undergoing UGIC surgery and provide a basis for implementation of the prehabilitation compound plan.METHODS A computerized search of databases including Web of Science,PubMed,EMBASE,The Cochrane Library,Cumulative Index to Nursing and Allied Health Literature,China National Knowledge Infrastructure,Wanfang,and Chinese Science and Technology Journal Database was used to collect clinical trials on the impact of prehabilitation on patients undergoing UGIC surgery.After screening,a meta-analysis was conducted using Review Manager 5.0 software,and linear regression analysis was performed on the prehabilitation duration and outcome indicators.RESULTS A total of 13 clinical trials were ultimately included,with 8 literature quality evaluations at A level and 5 literature quality evaluations at B level.The meta-analysis results showed that compared with conventional nursing,the prehabilitation group had higher six-minute walk distance,lower postoperative complications and mortality rates,and shorter hospital stays,with statistically significant differences;there were no statistically significant differences in intensive care unit monitoring time and albumin levels between the two groups;regression analysis between prehabilitation duration and outcome indicators showed no significant relationship.CONCLUSION Prehabilitation can improve the perioperative functional ability of patients with UGIC and promote postoperative recovery,but its impact on nutrition,psychology,and quality of life needs to be further explored through more high-quality trials;in addition,further research is needed on the prehabilitation time,location,and specific plan.
