In this paper,we establish some strong laws of large numbers,which are for nonindependent random variables under the framework of sublinear expectations.One of our main results is for blockwise m-dependent random vari...In this paper,we establish some strong laws of large numbers,which are for nonindependent random variables under the framework of sublinear expectations.One of our main results is for blockwise m-dependent random variables,and another is for sub-orthogonal random variables.Both extend the strong law of large numbers for independent random variables under sublinear expectations to the non-independent case.展开更多
Classical computation of electronic properties in large-scale materials remains challenging.Quantum computation has the potential to offer advantages in memory footprint and computational scaling.However,general and v...Classical computation of electronic properties in large-scale materials remains challenging.Quantum computation has the potential to offer advantages in memory footprint and computational scaling.However,general and viable quantum algorithms for simulating large-scale materials are still limited.We propose and implement random-state quantum algorithms to calculate electronic-structure properties of real materials.Using a random state circuit on a small number of qubits,we employ real-time evolution with first-order Trotter decomposition and Hadamard test to obtain electronic density of states,and we develop a modified quantum phase estimation algorithm to calculate real-space local density of states via direct quantum measurements.Furthermore,we validate these algorithms by numerically computing the density of states and spatial distributions of electronic states in graphene,twisted bilayer graphene quasicrystals,and fractal lattices,covering system sizes from hundreds to thousands of atoms.Our results manifest that the random-state quantum algorithms provide a general and qubit-efficient route to scalable simulations of electronic properties in large-scale periodic and aperiodic materials.展开更多
In this paper,we propose a random access scheme termed sign-compute diversity slotted ALOHA(SCDSA).The SCDSA scheme combines diversity transmission with compute-and-forward.Without considering the capture effect and m...In this paper,we propose a random access scheme termed sign-compute diversity slotted ALOHA(SCDSA).The SCDSA scheme combines diversity transmission with compute-and-forward.Without considering the capture effect and multiple user detection techniques,our scheme can reach a high throughput of 0.98 without feedback under finite frame size settings,where the upper bound on performance is 1.Moreover,a lower bound on throughput performance is derived,which is tight in some parameter settings and can be used to approximate theoretical performance.Simulation results validate our analysis and confirm the advantages of our proposed scheme.展开更多
Objective Previous studies link lower body mass index(BMI)with increased obsessive-compulsive disorder(OCD)risk,yet other body mass indicators may be more etioloically relevant.We dissected the causal association betw...Objective Previous studies link lower body mass index(BMI)with increased obsessive-compulsive disorder(OCD)risk,yet other body mass indicators may be more etioloically relevant.We dissected the causal association between body fat mass(FM)and OCD.Methods Summary statistics from genome-wide association studies of European ancestry were utilized to conduct two-sample Mendelian randomization analysis.Heterogeneity,horizontal pleiotropy,and sensitivity analyses were performed to assess the robustness.Results The inverse variance weighting method demonstrated that a genetically predicted decrease in FM was causally associated with an increased OCD risk[odds ratio(OR)=0.680,95%confidence interval(CI):0.528–0.875,P=0.003].Similar estimates were obtained using the weighted median approach(OR=0.633,95%CI:0.438–0.915,P=0.015).Each standard deviation increases in genetically predicted body fat percentage corresponded to a reduced OCD risk(OR=0.638,95%CI:0.455–0.896,P=0.009).The sensitivity analysis confirmed the robustness of these findings with no outlier instrument variables identified.Conclusion The negative causal association between FM and the risk of OCD suggests that the prevention or treatment of mental disorders should include not only the control of BMI but also fat distribution and body composition.展开更多
[Objectives]To investigate the potential causal relationship between psoriasis and common mental disorders,and to provide genetic epidemiological evidence for the early intervention of mental comorbidities.[Methods]Ba...[Objectives]To investigate the potential causal relationship between psoriasis and common mental disorders,and to provide genetic epidemiological evidence for the early intervention of mental comorbidities.[Methods]Based on publicly available large-scale GWAS data,a bidirectional Mendelian randomization(MR)approach was employed to assess the causal associations between psoriasis and major depressive disorder(MDD),bipolar disorder,schizophrenia,and anxiety disorders.The inverse variance weighted(IVW)method served as the primary analytical tool,supplemented by sensitivity analyses using MR-Egger and weighted median methods.Additionally,a subgroup analysis was conducted for psoriatic arthritis(PsA).[Results]Forward MR analysis revealed a significant positive causal association between the genetic predisposition to psoriasis and bipolar disorder as well as MDD,whereas no significant causal relationship was observed with schizophrenia or anxiety disorders.The reverse MR analysis found no causal effect of mental disorders on psoriasis.Subgroup analysis of PsA indicated that its genetic predisposition was significantly associated with the risk of bipolar disorder.The results of various sensitivity analyses and pleiotropy tests supported the robustness of the conclusions.[Conclusions]This study provides genetic evidence supporting a causal link between psoriasis and both MDD and bipolar disorder.In particular,patients with PsA are at a higher risk of developing bipolar disorder,highlighting the need to strengthen early screening and intervention for mental health in clinical management.展开更多
AIM:To investigate the causal effect of obesity on cataract risk and explores the potential mediating roles of metabolites using Mendelian randomization(MR).METHODS:Summary-level data from large-scale genome-wide asso...AIM:To investigate the causal effect of obesity on cataract risk and explores the potential mediating roles of metabolites using Mendelian randomization(MR).METHODS:Summary-level data from large-scale genome-wide association studies to examine the relationship between obesity and cataract were utilized.Obesity-related traits,including body mass index(BMI),waist-to-hip ratio(WHR),and waist circumference(WC).A two-sample MR approach was employed to assess the causal effect of obesity on cataract risk,while potential mediators were identified from suitable genome-wide association studies(GWAS)datasets.Additionally,a metabolic pathway analysis was conducted.RESULTS:An increase of 1 standard deviation(SD)in BMI,WHR,and WC was associated with a significantly higher risk of cataract(BMI:odds ratio(OR)1.0017,95%confidence interval(CI):1.0001-1.0032,P=0.0320;WHR:OR 1.0029,95%CI:1.0006-1.0051,P=0.0129;WC:OR 1.0020,95%CI:1.0001-1.0038,P=0.0390].These associations remained robust after adjusting for confounding factors in multivariable MR analysis.Furthermore,a two-step MR analysis identified eight potential metabolic mediators,with one mediator showing a significant causal role in the relationship between obesity and cataract.CONCLUSION:This work highlights the importance of addressing obesity as a modifiable risk factor for cataracts,particularly through metabolic pathways.展开更多
AIM:To comprehensively assess the relationship between asthma and myopia based on the National Health and Nutrition Examination Survey(NHANES)database combined with Mendelian randomization(MR).METHODS:Initially,20497 ...AIM:To comprehensively assess the relationship between asthma and myopia based on the National Health and Nutrition Examination Survey(NHANES)database combined with Mendelian randomization(MR).METHODS:Initially,20497 subjects from the complete questionnaire cycle in the NHANES database from 2005 to 2008 were included.By exclusion criteria,8460 subjects were screened with 1676 myopia samples and 6784 control samples.Subsequently,baseline characteristics,association analyses,risk stratification analyses,and receive operating characteristic curve(ROC)were used to investigate the associations between covariates and myopia.Then,the causal relationship was explored in depth by MR analysis,and was estimated the reliability by sensitivity analyses and directionality tests.RESULTS:Baseline characteristics illustrated a significant difference between myopia and controls for both asthma and covariates(excluding gender;P<0.05).The results in all three models indicated that asthma was strongly associated with myopia and the effect on myopia was not significantly confounded by other covariates[model 3:odd ratio(OR)=1.31;95%CI=1.07-1.62;P=0.0133].The risk stratification analysis again verified that asthma remained strongly associated with myopia and was a risk factor for myopia(P<0.05,OR>1).ROC proved that the model was accurate in its prediction[area under curve(AUC)=0.7].Subsequently,the causal relationship between them was statistically significant(P<0.05)according to the inverse variance weighted(IVW)method in MR.Scatterplot showed that asthma and myopia had significant positive causality and were not affected by confounders.Forest plot displayed an increasing risk of myopia on asthma(OR>1).The funnel plot demonstrated compliance with Mendel’s second law.Sensitivity analysis and directional analysis further confirmed the confidence of the MR analysis results and a unidirectional causal relationship between them.CONCLUSION:A significant association and causality between asthma and myopia is found through the NHANES database and MR analysis,which is important implications for public health policy development and clinical practice.展开更多
AIM:To explore the causal relationship between several possible behavioral factors and high myopia(HM)using multivariable Mendelian randomization(MVMR)approach and to find the mediators among them with mediation analy...AIM:To explore the causal relationship between several possible behavioral factors and high myopia(HM)using multivariable Mendelian randomization(MVMR)approach and to find the mediators among them with mediation analysis.METHODS:The causal effects of several behavioral factors,including screen time,education time,time spent outdoors,and physical activity,on the risk of HM using univariable Mendelian randomization(MR)and MVMR analyses were first assessed.Genome-wide association study summary statistics of serum metabolites were also used in mediation analysis to determine the extent to which serum metabolites mediate the effects of behavioral factors on HM.RESULTS:MR analyses indicated that both increased time spent outdoors and a higher frequency of moderate physical activity significantly reduced the risk of HM.Further MVMR analysis confirmed that moderate physical activity independently contributed to a lower risk of HM.Additionally,MR analyses identified 13 serum metabolites significantly associated with HM,of which 12 were lipids and one was an amino acid derivative.Mediation analysis revealed that six lipid metabolites mediated the protective effects of moderate physical activity on HM,with the highest mediation proportion observed for 1-(1-enyl-palmitoyl)-GPC(p-16:0;30.83%).CONCLUSION:This study suggests that in addition to outdoor time,moderate physical activity habits may have an independent protective effect against HM and pointed to lipid metabolites as priority targets for the prevention due to low physical activity.These results emphasize the importance of physical activity and metabolic health in HM and underscore the need for further study of these complex associations.展开更多
This paper introduces a framework for modeling random fields,with a particular emphasis on analyzing anisotropic spatial variability.It establishes a clear connection between the correlation function and the Kriging v...This paper introduces a framework for modeling random fields,with a particular emphasis on analyzing anisotropic spatial variability.It establishes a clear connection between the correlation function and the Kriging variogram across various anisotropic modes,providing mathematical models to enhance our understanding of random fields.A new anisotropy index,called LSAI,is introduced to quantify anisotropy based on the autocorrelation length and the orientation of the principal axes within the variogram.An LSAI value closer to one indicates a lower degree of anisotropy.The present study examines how the degree of anisotropy varies with different autocorrelation lengths and angles between the principal axes,providing valuable insights into these relationships.To improve the accuracy of parameter probability distribution estimations,this study integrates limited field test data using a Bayesian inference approach.Additionally,the Markov chain Monte Carlo simulation method is employed to develop a conditional random field(CRF)for the deformation modulus.By incorporating data from field bearing plate tests,the posterior variance data for the deformation modulus are derived.This process facilitates the construction of a detailed and reliable CRF for the deformation modulus.展开更多
The advent of 5G technology has significantly enhanced the transmission of images over networks,expanding data accessibility and exposure across various applications in digital technology and social media.Consequently...The advent of 5G technology has significantly enhanced the transmission of images over networks,expanding data accessibility and exposure across various applications in digital technology and social media.Consequently,the protection of sensitive data has become increasingly critical.Regardless of the complexity of the encryption algorithm used,a robust and highly secure encryption key is essential,with randomness and key space being crucial factors.This paper proposes a new Robust Deoxyribonucleic Acid(RDNA)nucleotide-based encryption method.The RDNA encryption method leverages the unique properties of DNA nucleotides,including their inherent randomness and extensive key space,to generate a highly secure encryption key.By employing transposition and substitution operations,the RDNA method ensures significant diffusion and confusion in the encrypted images.Additionally,it utilises a pseudorandom generation technique based on the random sequence of nucleotides in the DNA secret key.The performance of the RDNA encryption method is evaluated through various statistical and visual tests,and compared against established encryption methods such as 3DES,AES,and a DNA-based method.Experimental results demonstrate that the RDNA encryption method outperforms its rivals in the literature,and achieves superior performance in terms of information entropy,avalanche effect,encryption execution time,and correlation reduction,while maintaining competitive values for NMAE,PSNR,NPCR,and UACI.The high degree of randomness and sensitivity to key changes inherent in the RDNA method offers enhanced security,making it highly resistant to brute force and differential attacks.展开更多
Slope units are divided according to the real topography and have clear geological characteristics,making them ideal units for evaluating the susceptibility to geological disasters.Based on the results of automaticall...Slope units are divided according to the real topography and have clear geological characteristics,making them ideal units for evaluating the susceptibility to geological disasters.Based on the results of automatically and manually corrected hydrological slope unit division,the Longhua District,Shenzhen City,Guangdong Province,was selected as the study area.A total of 15 influencing factors,namely Fluctuation,slope,slope aspect,curvature,topographic witness index(TWI),stream power index(SPI),topographic roughness index(TRI),annual average rainfall,distance to water system,engineering rock group,distance to fault,land use,normalized difference vegetation index(NDVI),nighttime light,and distance to road,were selected as evaluation indicators.The information volume model(IV)and random points were used to select non-geological disaster units,and then the random forest model(RF)was used to evaluate the susceptibility to geological disasters.The automatic slope unit and the hydrological slope unit were compared and analyzed in the random forest and information volume random forest models.The results show that the area under the curve(AUC)values of the automatic slope unit evaluation results are 0.931 for the IV-RF model and 0.716 for the RF model,which are 0.6%(IV-RF model)and 1.9%(RF model)higher than those for the hydrological slope unit.Based on a comparison of the evaluation methods based on the two types of slope units,the hydrological slope unit evaluation method based on manual correction is highly subjective,is complicated to operate,and has a low evaluation accuracy,whereas the evaluation method based on automatic slope unit division is efficient and accurate,is suitable for large-scale efficient geological disaster evaluation,and can better deal with the problem of geological disaster susceptibility evaluation.展开更多
AIM:To investigate the potential causal associations between 41 inflammatory cytokines and myopia using a two-sample Mendelian randomization(MR)approach.METHODS:Publicly available genome-wide association study(GWAS)da...AIM:To investigate the potential causal associations between 41 inflammatory cytokines and myopia using a two-sample Mendelian randomization(MR)approach.METHODS:Publicly available genome-wide association study(GWAS)datasets were utilized for this two-sample MR analysis.Inflammatory cytokine-related GWAS data were extracted from The University of Bristol’s Research Data Repository,and myopia-related GWAS data were obtained from the FinnGen project.Single nucleotide polymorphisms(SNPs)associated with inflammatory cytokines were systematically selected as instrumental variables(IVs)based on three rigorous criteria:relevance,independence,and exclusion of pleiotropy.Five MR methods were employed for causal inference:the inverse-variance weighted(IVW)method as the primary analysis,supplemented by MREgger regression,weighted median estimator,simple mode,and weighted mode approaches.Sensitivity analyses were performed to evaluate the robustness of the causal estimates.RESULTS:A total of 773 myopia-associated SNPs were identified.MR analysis revealed that higher levels of macrophage inflammatory protein 1-α(MIP-1α)were associated with a 17%reduced risk of myopia[odds ratio(OR)=0.83;95%confidence interval(CI):0.69-0.99;P<0.05].In contrast,elevated levels of eotaxin(OR=1.26;95%CI:1.07-1.47;P<0.01),stromal cell-derived factor-1α(SDF-1α;OR=1.68;95%CI:1.08-2.62;P<0.05),and interleukin-2 receptor subunit alpha(IL-2Rα;OR=1.25;95%CI:1.01-1.53;P<0.05)were significantly associated with an increased risk of myopia.Sensitivity analyses confirmed the reliability of these results.CONCLUSION:This study provides evidence supporting a causal relationship between specific inflammatory cytokines and myopia.MIP-1αmay act as a protective factor against myopia,while eotaxin,SDF-1α,and IL-2Rαare potential risk factors for myopia.These findings emphasize the critical role of inflammatory pathways in the pathogenesis of myopia,offering novel insights for the development of preventive and therapeutic strategies for myopia.展开更多
Background Recent studies have suggested a potential role of the oral microbiome in the development of cardiovascular diseases.This study aims to investigate the association between oral microbiota and cardiovascular ...Background Recent studies have suggested a potential role of the oral microbiome in the development of cardiovascular diseases.This study aims to investigate the association between oral microbiota and cardiovascular disease risk,including atrial fibrillation,myocardial infarction,chronic heart failure,and hypertension.Methods We analyzed GWAS data from East Asian populations'oral microbiome,involving 2,017 tongue and 1,915 saliva samples from 2,984 individuals with whole-genome sequencing.Additionally,we sourced cardiovascular disease GWAS data from NBDC,including atrial fibrillation(8,180 cases,28,621 controls),myocardial infarction(14,992 cases,146,214 controls),chronic heart failure(10,540 cases,168,186 controls),and systolic blood pressure(145,505 individuals).Results Several oral microbiota taxa were found to be significantly associated with cardiovascular disease outcomes.Specific microbiota,such as Centipeda,Corynebacterium,and Pseudomonas E,were negatively correlated with heart failure.In contrast,taxa like Neisseria D and Actinomyces were associated with an increased risk of atrial fibrillation and myocardial infarction.Additionally,certain oral microbiota showed correlations with changes in blood pressure,highlighting their potential role in hypertension.Conclusion Our findings suggest that the oral microbiota may influence the development and progression of cardiovascular diseases,providing new insights into the potential impact of oral health on cardiovascular risk.展开更多
Objectives This study aimed to design and evaluate a detection system for the accidental dislodgement of head-and-neck medical supplies through hand position recognition and tracking in Intensive Care Unit(ICU)patient...Objectives This study aimed to design and evaluate a detection system for the accidental dislodgement of head-and-neck medical supplies through hand position recognition and tracking in Intensive Care Unit(ICU)patients.Methods We conducted a single-center,prospective,parallel-group feasibility randomized controlled trial.We recruited 80 participants using convenience sampling from the ICU of a hospital in Ningbo City,Zhejiang Province,between March 2025 and June 2025,and they were randomly assigned to either the control group(routine care)or the intervention group(routine care plus image recognition-based detection system).The system continuously tracked patients’hand positions via bedside cameras and generated real-time alarms when hands entered predefined risk zones,notifying on-duty nurses to enable early intervention.System stability was assessed by continuous system uptime;system performance and clinical feasibility were evaluated by the frequencies of risk actions and accidental dislodgement of medical supplies(ADMS).Results All 80 participants completed the intervention,with 40 patients in each group.The baseline characteristics and median observation time of the two groups were balanced(intervention group:48 h/patient vs.control group:49 h/patient).Compared with the control group,the intervention group showed fewer ADMS(2/40 vs.9/40)and detected more risk actions per 100 h(36 vs.25);all system-detected events had corroborating images with complete concordance on manual review,and all nurse-recorded hand-contact events were accurately captured.Conclusions The study demonstrated that the image recognition-based detection system can function stably in clinical settings,providing accurate and continuous surveillance while supporting the early detection of risk actions.By reducing the observation burden and offering real-time cognitive support,the system complements routine nursing care and serves as an additional safety measure in ICU practice.With further optimization and larger multicenter validation,this approach could have the potential to make a significant contribution to the development of smart ICUs and the broader digital transformation of nursing care.展开更多
钢拱桥的线形监测是桥梁健康监测系统的重要组成部分。运用三维激光扫描技术,融合随机抽样一致(random sample consensus,RANSAC)算法对传统的具有噪声的基于密度的聚类方法(density-based spatial clustering of applications with noi...钢拱桥的线形监测是桥梁健康监测系统的重要组成部分。运用三维激光扫描技术,融合随机抽样一致(random sample consensus,RANSAC)算法对传统的具有噪声的基于密度的聚类方法(density-based spatial clustering of applications with noise,DBSCAN)算法进行改进,对钢拱桥拱肋线形进行提取。三维激光点云数据具有全面性和细节体现的优势,能够完整地呈现桥梁结构的形状和变形信息,融合RANSAC的改进DBSCAN算法根据钢拱桥结构特征对聚类结果进行约束,能够很好地实现删除离散点及桥面、横撑、横联和腹杆部分的点云这一目的。根据融合RANSAC的改进DBSCAN算法提取出的点云进行关键点拟合,与人工提取结果进行对比,拱肋关键点提取误差均在毫米级,最大误差为9.2 mm,最小误差为0.1 mm,此提取方法能够更加准确有效地完成钢拱桥线形提取,使线形提取精度达到毫米级,大大降低了人力成本和时间成本,对钢拱桥的复杂结构有更好的鲁棒性,能很好地适应实际生产需求。展开更多
文摘In this paper,we establish some strong laws of large numbers,which are for nonindependent random variables under the framework of sublinear expectations.One of our main results is for blockwise m-dependent random variables,and another is for sub-orthogonal random variables.Both extend the strong law of large numbers for independent random variables under sublinear expectations to the non-independent case.
基金supported by the Major Project for the Integration of ScienceEducation and Industry (Grant No.2025ZDZX02)。
文摘Classical computation of electronic properties in large-scale materials remains challenging.Quantum computation has the potential to offer advantages in memory footprint and computational scaling.However,general and viable quantum algorithms for simulating large-scale materials are still limited.We propose and implement random-state quantum algorithms to calculate electronic-structure properties of real materials.Using a random state circuit on a small number of qubits,we employ real-time evolution with first-order Trotter decomposition and Hadamard test to obtain electronic density of states,and we develop a modified quantum phase estimation algorithm to calculate real-space local density of states via direct quantum measurements.Furthermore,we validate these algorithms by numerically computing the density of states and spatial distributions of electronic states in graphene,twisted bilayer graphene quasicrystals,and fractal lattices,covering system sizes from hundreds to thousands of atoms.Our results manifest that the random-state quantum algorithms provide a general and qubit-efficient route to scalable simulations of electronic properties in large-scale periodic and aperiodic materials.
文摘In this paper,we propose a random access scheme termed sign-compute diversity slotted ALOHA(SCDSA).The SCDSA scheme combines diversity transmission with compute-and-forward.Without considering the capture effect and multiple user detection techniques,our scheme can reach a high throughput of 0.98 without feedback under finite frame size settings,where the upper bound on performance is 1.Moreover,a lower bound on throughput performance is derived,which is tight in some parameter settings and can be used to approximate theoretical performance.Simulation results validate our analysis and confirm the advantages of our proposed scheme.
基金supported by the Yanzhao Gold Talent Project of Hebei Province(NO.HJZD202506)。
文摘Objective Previous studies link lower body mass index(BMI)with increased obsessive-compulsive disorder(OCD)risk,yet other body mass indicators may be more etioloically relevant.We dissected the causal association between body fat mass(FM)and OCD.Methods Summary statistics from genome-wide association studies of European ancestry were utilized to conduct two-sample Mendelian randomization analysis.Heterogeneity,horizontal pleiotropy,and sensitivity analyses were performed to assess the robustness.Results The inverse variance weighting method demonstrated that a genetically predicted decrease in FM was causally associated with an increased OCD risk[odds ratio(OR)=0.680,95%confidence interval(CI):0.528–0.875,P=0.003].Similar estimates were obtained using the weighted median approach(OR=0.633,95%CI:0.438–0.915,P=0.015).Each standard deviation increases in genetically predicted body fat percentage corresponded to a reduced OCD risk(OR=0.638,95%CI:0.455–0.896,P=0.009).The sensitivity analysis confirmed the robustness of these findings with no outlier instrument variables identified.Conclusion The negative causal association between FM and the risk of OCD suggests that the prevention or treatment of mental disorders should include not only the control of BMI but also fat distribution and body composition.
文摘[Objectives]To investigate the potential causal relationship between psoriasis and common mental disorders,and to provide genetic epidemiological evidence for the early intervention of mental comorbidities.[Methods]Based on publicly available large-scale GWAS data,a bidirectional Mendelian randomization(MR)approach was employed to assess the causal associations between psoriasis and major depressive disorder(MDD),bipolar disorder,schizophrenia,and anxiety disorders.The inverse variance weighted(IVW)method served as the primary analytical tool,supplemented by sensitivity analyses using MR-Egger and weighted median methods.Additionally,a subgroup analysis was conducted for psoriatic arthritis(PsA).[Results]Forward MR analysis revealed a significant positive causal association between the genetic predisposition to psoriasis and bipolar disorder as well as MDD,whereas no significant causal relationship was observed with schizophrenia or anxiety disorders.The reverse MR analysis found no causal effect of mental disorders on psoriasis.Subgroup analysis of PsA indicated that its genetic predisposition was significantly associated with the risk of bipolar disorder.The results of various sensitivity analyses and pleiotropy tests supported the robustness of the conclusions.[Conclusions]This study provides genetic evidence supporting a causal link between psoriasis and both MDD and bipolar disorder.In particular,patients with PsA are at a higher risk of developing bipolar disorder,highlighting the need to strengthen early screening and intervention for mental health in clinical management.
基金Supported by the National Natural Science Foundation of China(No.82501261)Medical Research Projects of the Jiangsu Provincial Health Commission(No.M2024041).
文摘AIM:To investigate the causal effect of obesity on cataract risk and explores the potential mediating roles of metabolites using Mendelian randomization(MR).METHODS:Summary-level data from large-scale genome-wide association studies to examine the relationship between obesity and cataract were utilized.Obesity-related traits,including body mass index(BMI),waist-to-hip ratio(WHR),and waist circumference(WC).A two-sample MR approach was employed to assess the causal effect of obesity on cataract risk,while potential mediators were identified from suitable genome-wide association studies(GWAS)datasets.Additionally,a metabolic pathway analysis was conducted.RESULTS:An increase of 1 standard deviation(SD)in BMI,WHR,and WC was associated with a significantly higher risk of cataract(BMI:odds ratio(OR)1.0017,95%confidence interval(CI):1.0001-1.0032,P=0.0320;WHR:OR 1.0029,95%CI:1.0006-1.0051,P=0.0129;WC:OR 1.0020,95%CI:1.0001-1.0038,P=0.0390].These associations remained robust after adjusting for confounding factors in multivariable MR analysis.Furthermore,a two-step MR analysis identified eight potential metabolic mediators,with one mediator showing a significant causal role in the relationship between obesity and cataract.CONCLUSION:This work highlights the importance of addressing obesity as a modifiable risk factor for cataracts,particularly through metabolic pathways.
基金Supported by the Hainan Provincial Natural Science Foundation of China(No.825RC898)Hainan Province Clinical Medical Center。
文摘AIM:To comprehensively assess the relationship between asthma and myopia based on the National Health and Nutrition Examination Survey(NHANES)database combined with Mendelian randomization(MR).METHODS:Initially,20497 subjects from the complete questionnaire cycle in the NHANES database from 2005 to 2008 were included.By exclusion criteria,8460 subjects were screened with 1676 myopia samples and 6784 control samples.Subsequently,baseline characteristics,association analyses,risk stratification analyses,and receive operating characteristic curve(ROC)were used to investigate the associations between covariates and myopia.Then,the causal relationship was explored in depth by MR analysis,and was estimated the reliability by sensitivity analyses and directionality tests.RESULTS:Baseline characteristics illustrated a significant difference between myopia and controls for both asthma and covariates(excluding gender;P<0.05).The results in all three models indicated that asthma was strongly associated with myopia and the effect on myopia was not significantly confounded by other covariates[model 3:odd ratio(OR)=1.31;95%CI=1.07-1.62;P=0.0133].The risk stratification analysis again verified that asthma remained strongly associated with myopia and was a risk factor for myopia(P<0.05,OR>1).ROC proved that the model was accurate in its prediction[area under curve(AUC)=0.7].Subsequently,the causal relationship between them was statistically significant(P<0.05)according to the inverse variance weighted(IVW)method in MR.Scatterplot showed that asthma and myopia had significant positive causality and were not affected by confounders.Forest plot displayed an increasing risk of myopia on asthma(OR>1).The funnel plot demonstrated compliance with Mendel’s second law.Sensitivity analysis and directional analysis further confirmed the confidence of the MR analysis results and a unidirectional causal relationship between them.CONCLUSION:A significant association and causality between asthma and myopia is found through the NHANES database and MR analysis,which is important implications for public health policy development and clinical practice.
基金Supported by the Central High Level Hospital Clinical Research Funding(No.BJ-2024-089).
文摘AIM:To explore the causal relationship between several possible behavioral factors and high myopia(HM)using multivariable Mendelian randomization(MVMR)approach and to find the mediators among them with mediation analysis.METHODS:The causal effects of several behavioral factors,including screen time,education time,time spent outdoors,and physical activity,on the risk of HM using univariable Mendelian randomization(MR)and MVMR analyses were first assessed.Genome-wide association study summary statistics of serum metabolites were also used in mediation analysis to determine the extent to which serum metabolites mediate the effects of behavioral factors on HM.RESULTS:MR analyses indicated that both increased time spent outdoors and a higher frequency of moderate physical activity significantly reduced the risk of HM.Further MVMR analysis confirmed that moderate physical activity independently contributed to a lower risk of HM.Additionally,MR analyses identified 13 serum metabolites significantly associated with HM,of which 12 were lipids and one was an amino acid derivative.Mediation analysis revealed that six lipid metabolites mediated the protective effects of moderate physical activity on HM,with the highest mediation proportion observed for 1-(1-enyl-palmitoyl)-GPC(p-16:0;30.83%).CONCLUSION:This study suggests that in addition to outdoor time,moderate physical activity habits may have an independent protective effect against HM and pointed to lipid metabolites as priority targets for the prevention due to low physical activity.These results emphasize the importance of physical activity and metabolic health in HM and underscore the need for further study of these complex associations.
基金supported by the Doctoral Research Funds for Nanchang HangKong University,China(Grant No.EA202411211)support is gratefully acknowledged.
文摘This paper introduces a framework for modeling random fields,with a particular emphasis on analyzing anisotropic spatial variability.It establishes a clear connection between the correlation function and the Kriging variogram across various anisotropic modes,providing mathematical models to enhance our understanding of random fields.A new anisotropy index,called LSAI,is introduced to quantify anisotropy based on the autocorrelation length and the orientation of the principal axes within the variogram.An LSAI value closer to one indicates a lower degree of anisotropy.The present study examines how the degree of anisotropy varies with different autocorrelation lengths and angles between the principal axes,providing valuable insights into these relationships.To improve the accuracy of parameter probability distribution estimations,this study integrates limited field test data using a Bayesian inference approach.Additionally,the Markov chain Monte Carlo simulation method is employed to develop a conditional random field(CRF)for the deformation modulus.By incorporating data from field bearing plate tests,the posterior variance data for the deformation modulus are derived.This process facilitates the construction of a detailed and reliable CRF for the deformation modulus.
文摘The advent of 5G technology has significantly enhanced the transmission of images over networks,expanding data accessibility and exposure across various applications in digital technology and social media.Consequently,the protection of sensitive data has become increasingly critical.Regardless of the complexity of the encryption algorithm used,a robust and highly secure encryption key is essential,with randomness and key space being crucial factors.This paper proposes a new Robust Deoxyribonucleic Acid(RDNA)nucleotide-based encryption method.The RDNA encryption method leverages the unique properties of DNA nucleotides,including their inherent randomness and extensive key space,to generate a highly secure encryption key.By employing transposition and substitution operations,the RDNA method ensures significant diffusion and confusion in the encrypted images.Additionally,it utilises a pseudorandom generation technique based on the random sequence of nucleotides in the DNA secret key.The performance of the RDNA encryption method is evaluated through various statistical and visual tests,and compared against established encryption methods such as 3DES,AES,and a DNA-based method.Experimental results demonstrate that the RDNA encryption method outperforms its rivals in the literature,and achieves superior performance in terms of information entropy,avalanche effect,encryption execution time,and correlation reduction,while maintaining competitive values for NMAE,PSNR,NPCR,and UACI.The high degree of randomness and sensitivity to key changes inherent in the RDNA method offers enhanced security,making it highly resistant to brute force and differential attacks.
文摘Slope units are divided according to the real topography and have clear geological characteristics,making them ideal units for evaluating the susceptibility to geological disasters.Based on the results of automatically and manually corrected hydrological slope unit division,the Longhua District,Shenzhen City,Guangdong Province,was selected as the study area.A total of 15 influencing factors,namely Fluctuation,slope,slope aspect,curvature,topographic witness index(TWI),stream power index(SPI),topographic roughness index(TRI),annual average rainfall,distance to water system,engineering rock group,distance to fault,land use,normalized difference vegetation index(NDVI),nighttime light,and distance to road,were selected as evaluation indicators.The information volume model(IV)and random points were used to select non-geological disaster units,and then the random forest model(RF)was used to evaluate the susceptibility to geological disasters.The automatic slope unit and the hydrological slope unit were compared and analyzed in the random forest and information volume random forest models.The results show that the area under the curve(AUC)values of the automatic slope unit evaluation results are 0.931 for the IV-RF model and 0.716 for the RF model,which are 0.6%(IV-RF model)and 1.9%(RF model)higher than those for the hydrological slope unit.Based on a comparison of the evaluation methods based on the two types of slope units,the hydrological slope unit evaluation method based on manual correction is highly subjective,is complicated to operate,and has a low evaluation accuracy,whereas the evaluation method based on automatic slope unit division is efficient and accurate,is suitable for large-scale efficient geological disaster evaluation,and can better deal with the problem of geological disaster susceptibility evaluation.
文摘AIM:To investigate the potential causal associations between 41 inflammatory cytokines and myopia using a two-sample Mendelian randomization(MR)approach.METHODS:Publicly available genome-wide association study(GWAS)datasets were utilized for this two-sample MR analysis.Inflammatory cytokine-related GWAS data were extracted from The University of Bristol’s Research Data Repository,and myopia-related GWAS data were obtained from the FinnGen project.Single nucleotide polymorphisms(SNPs)associated with inflammatory cytokines were systematically selected as instrumental variables(IVs)based on three rigorous criteria:relevance,independence,and exclusion of pleiotropy.Five MR methods were employed for causal inference:the inverse-variance weighted(IVW)method as the primary analysis,supplemented by MREgger regression,weighted median estimator,simple mode,and weighted mode approaches.Sensitivity analyses were performed to evaluate the robustness of the causal estimates.RESULTS:A total of 773 myopia-associated SNPs were identified.MR analysis revealed that higher levels of macrophage inflammatory protein 1-α(MIP-1α)were associated with a 17%reduced risk of myopia[odds ratio(OR)=0.83;95%confidence interval(CI):0.69-0.99;P<0.05].In contrast,elevated levels of eotaxin(OR=1.26;95%CI:1.07-1.47;P<0.01),stromal cell-derived factor-1α(SDF-1α;OR=1.68;95%CI:1.08-2.62;P<0.05),and interleukin-2 receptor subunit alpha(IL-2Rα;OR=1.25;95%CI:1.01-1.53;P<0.05)were significantly associated with an increased risk of myopia.Sensitivity analyses confirmed the reliability of these results.CONCLUSION:This study provides evidence supporting a causal relationship between specific inflammatory cytokines and myopia.MIP-1αmay act as a protective factor against myopia,while eotaxin,SDF-1α,and IL-2Rαare potential risk factors for myopia.These findings emphasize the critical role of inflammatory pathways in the pathogenesis of myopia,offering novel insights for the development of preventive and therapeutic strategies for myopia.
基金supported by the National Natural Science Foundation of China(Grant No.82500432)the Heilongjiang Provincial Health Commission Scientific Research Project(Grant No.20240303010111).
文摘Background Recent studies have suggested a potential role of the oral microbiome in the development of cardiovascular diseases.This study aims to investigate the association between oral microbiota and cardiovascular disease risk,including atrial fibrillation,myocardial infarction,chronic heart failure,and hypertension.Methods We analyzed GWAS data from East Asian populations'oral microbiome,involving 2,017 tongue and 1,915 saliva samples from 2,984 individuals with whole-genome sequencing.Additionally,we sourced cardiovascular disease GWAS data from NBDC,including atrial fibrillation(8,180 cases,28,621 controls),myocardial infarction(14,992 cases,146,214 controls),chronic heart failure(10,540 cases,168,186 controls),and systolic blood pressure(145,505 individuals).Results Several oral microbiota taxa were found to be significantly associated with cardiovascular disease outcomes.Specific microbiota,such as Centipeda,Corynebacterium,and Pseudomonas E,were negatively correlated with heart failure.In contrast,taxa like Neisseria D and Actinomyces were associated with an increased risk of atrial fibrillation and myocardial infarction.Additionally,certain oral microbiota showed correlations with changes in blood pressure,highlighting their potential role in hypertension.Conclusion Our findings suggest that the oral microbiota may influence the development and progression of cardiovascular diseases,providing new insights into the potential impact of oral health on cardiovascular risk.
文摘Objectives This study aimed to design and evaluate a detection system for the accidental dislodgement of head-and-neck medical supplies through hand position recognition and tracking in Intensive Care Unit(ICU)patients.Methods We conducted a single-center,prospective,parallel-group feasibility randomized controlled trial.We recruited 80 participants using convenience sampling from the ICU of a hospital in Ningbo City,Zhejiang Province,between March 2025 and June 2025,and they were randomly assigned to either the control group(routine care)or the intervention group(routine care plus image recognition-based detection system).The system continuously tracked patients’hand positions via bedside cameras and generated real-time alarms when hands entered predefined risk zones,notifying on-duty nurses to enable early intervention.System stability was assessed by continuous system uptime;system performance and clinical feasibility were evaluated by the frequencies of risk actions and accidental dislodgement of medical supplies(ADMS).Results All 80 participants completed the intervention,with 40 patients in each group.The baseline characteristics and median observation time of the two groups were balanced(intervention group:48 h/patient vs.control group:49 h/patient).Compared with the control group,the intervention group showed fewer ADMS(2/40 vs.9/40)and detected more risk actions per 100 h(36 vs.25);all system-detected events had corroborating images with complete concordance on manual review,and all nurse-recorded hand-contact events were accurately captured.Conclusions The study demonstrated that the image recognition-based detection system can function stably in clinical settings,providing accurate and continuous surveillance while supporting the early detection of risk actions.By reducing the observation burden and offering real-time cognitive support,the system complements routine nursing care and serves as an additional safety measure in ICU practice.With further optimization and larger multicenter validation,this approach could have the potential to make a significant contribution to the development of smart ICUs and the broader digital transformation of nursing care.
