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
We study a finite number of independent random walks with subexponentially distributed increments and negative drifts.We extend the one-dimensional results to finite and fully general stopping times.Assuming that the ...We study a finite number of independent random walks with subexponentially distributed increments and negative drifts.We extend the one-dimensional results to finite and fully general stopping times.Assuming that the distribution of the lengths of these intervals is relatively light compared to the distribution of the increments of the random walks,we derive the asymptotic tail distribution of the partial maximum sum over the random time interval.展开更多
Objective:The incidence and mortality of colorectal carcinoma(CRC)continue to rise globally,highlighting the need to identify modifiable risk factors for early detection and prevention.Previous studies have demonstrat...Objective:The incidence and mortality of colorectal carcinoma(CRC)continue to rise globally,highlighting the need to identify modifiable risk factors for early detection and prevention.Previous studies have demonstrated significant associations between CRC risk and various serum metabolites as well as inflammatory cytokines;however,due to limitations in study design and potential confounding factors,the causal relationships remain unclear.This study aims to investigate the causal relationships between inflammatory cytokines,serum metabolites,and CRC risk,providing a theoretical basis for the development of novel early diagnostic biomarkers and therapeutic targets.Methods:A two-sample Mendelian randomization(MR)design was applied using summary statistics from genome-wide association studies(GWAS).Instrumental variables(IVs)were derived from:1)metabolomics GWAS data of 1400 serum metabolites(n=8299);2)cytokine GWAS data of 91 inflammatory factors(n=14824);and 3)CRC risk data from the FinnGen consortium(6847 cases and 314193 controls).The primary analysis was conducted using the inverse-variance weighted(IVW)method,with sensitivity analyses performed using MR Egger regression and the weighted median method.Effect estimates including odds ratios(OR),95%confidence intervals(CI),and false discovery rates(FDR)were calculated.Results:MR analysis indicated that higher levels of axin-1(AXIN1)(OR=0.84195%CI 0.714 to 0.991)and Fms-related tyrosine kinase 3 ligand(Flt3L)(OR=0.916,95%CI 0.844 to 0.994)were associated with a reduced risk of CRC.In contrast,higher levels of Delta/Notchlike epidermal growth factor-related receptor(DNER)(OR=1.119,95%CI 1.009 to 1.241)and vascular endothelial growth factor A(VEGF-A)(OR=1.078,95%CI 1.011 to 1.150)were associated with an increased risk of CRC(all P<0.05).Metabolomics association analysis further identified 144 serum metabolites significantly correlated with these four key inflammatory cytokines(FDR<0.05),suggesting that they may regulate CRC risk through inflammatory pathways.Conclusion:Specific inflammatory cytokines and serum metabolites have causal relationships with the risk of CRC.These findings provide insights for further exploration of potential risk factors and the development of effective prevention strategies for CRC.展开更多
The important work of Yu,et al.[1]who presented one of the first randomized controlled trials(RCTs)to directly compare robot-assisted and manual percutaneous coronary intervention(PCI),is commendable;offering importan...The important work of Yu,et al.[1]who presented one of the first randomized controlled trials(RCTs)to directly compare robot-assisted and manual percutaneous coronary intervention(PCI),is commendable;offering important insights into the feasibility and outcomes of this emerging technology.While the analysis is timely,several issues warrant further consideration.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
Although diet and gut microbial composition have been linked to chronic respiratory diseases,these associations remain difficult to interpret because of confounding and reverse causation.The gut-lung axis provides a p...Although diet and gut microbial composition have been linked to chronic respiratory diseases,these associations remain difficult to interpret because of confounding and reverse causation.The gut-lung axis provides a plausible framework for this interaction,yet direct genetic evidence is limited.Using a two-step,two-sample Mendelian randomization(MR)framework,supplemented by multivariable MR(MVMR)to adjust for pleiotropic effects and Benjamini-Hochberg false discovery rate(FDR)correction for multiple testing,we assessed the causal contributions of dietary habits and gut microbial taxa to major chronic respiratory diseases.We identified 22 dietary factors with causal effects on disease risk and 225 microbial taxa that acted as independent risk or protective contributors.Mediation analyses further showed that the effects of 12 dietary habits were transmitted through 32 specific microbial taxa.Notably,genetically predicted pork intake increased the risk of chronic obstructive pulmonary disease(COPD)(OR=10.53,95%CI[8.54,13.00]),an effect partly mediated by elevated abundance of CAG-485 sp002404675.In contrast,bread consumption conferred protection against asthma(OR=0.68,95%CI[0.64,0.72]),whereas this benefit was offset by approximately 45%through a pathway involving reduced Veillonella abundance.Collectively,these findings provide genetic support for the gut-lung axis and demonstrate that the gut microbiome functions as a causal mediator linking diet to chronic respiratory disease risk.However,since this study was based on individuals of European ancestry,caution is warranted when generalizing these causal estimates to non-European populations,such as East Asian groups.This work suggests new opportunities for microbiota-targeted prevention and therapeutic strategies.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
Quantile regression(QR)has become an important tool to measure dependence of response variable's quantiles on a number of predictors for heterogeneous data,especially heavy-tailed data and outliers.However,it is q...Quantile regression(QR)has become an important tool to measure dependence of response variable's quantiles on a number of predictors for heterogeneous data,especially heavy-tailed data and outliers.However,it is quite challenging to make statistical inference on distributed high-dimensional QR with missing data due to the distributed nature,sparsity and missingness of data and nondifferentiable quantile loss function.To overcome the challenge,this paper develops a communicationefficient method to select variables and estimate parameters by utilizing a smooth function to approximate the non-differentiable quantile loss function and incorporating the idea of the inverse probability weighting and the penalty function.The proposed approach has three merits.First,it is both computationally and communicationally efficient because only the first-and second-order information of the approximate objective function are communicated at each iteration.Second,the proposed estimators possess the oracle property after a limited number of iterations without constraint on the number of machines.Third,the proposed method simultaneously selects variables and estimates parameters within a distributed framework,ensuring robustness to the specified response probability or propensity score function of the missing data mechanism.Simulation studies and a real example are used to illustrate the effectiveness of the proposed methodologies.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
Although the concentration of fine particulate matter(PM_(2.5))is reducing continuously,the proportion of secondary organic aerosols(SOA)in PM_(2.5) and the O_(3) levels are increasing.This is causing severe complex a...Although the concentration of fine particulate matter(PM_(2.5))is reducing continuously,the proportion of secondary organic aerosols(SOA)in PM_(2.5) and the O_(3) levels are increasing.This is causing severe complex atmospheric pollution in North China.It is essential to identify and quantify the driving factors of SOA and O_(3),including the various pollution sources and meteorological factors.PM_(2.5) and volatile organic compounds(VOCs)samples were collected simultaneously in three cities in Shandong Province during different pollution scenarios from 2021 to 2023.Then,the carbonaceous aerosol and 99 VOC species were analyzed.Random forest(RF)combined with positive matrix factorization and an observation-based model(OBM)were used to quantify the key drivers of SOA and O_(3).Aromatic hydrocarbons were the main contributors to secondary organic aerosol potential(74.3%-89.9%),whereas alkenes contributed the most to the ozone formation potential(27.0%-62.3%).The RF modeling identified temperature and NOx as the dominant drivers of ozone formation.These accounted for 47.8%and 17.4%,respectively.Temperature showed a positive correlation with O_(3) because an increase in temperature can promote ozone formation.NOx had a significant negative correlation with O_(3),which was consistent with the conclusions from the sensitivity analysis of the OBM.The dominant contributors to SOA were vehicle emissions,solvent use,and industrial emissions.These accounted for 43.9%,18.2%,and 10.5%,respectively.An evident positive correlation existed between these emission sources and SOA.展开更多
OBJECTIVE:To assess the efficacy of point application therapy(PAT)in alleviating the exacerbation of chronic respiratory diseases represented by bronchial asthma.METHODS:In this multicenter randomized placebocontrolle...OBJECTIVE:To assess the efficacy of point application therapy(PAT)in alleviating the exacerbation of chronic respiratory diseases represented by bronchial asthma.METHODS:In this multicenter randomized placebocontrolled trial,eligible bronchial asthma patients received placebo PAT on the dog days of the first summer to establish a baseline,and then patients who continued to participate in the trial and repassed the eligibility review were randomized to receive regular or placebo PAT in the next two consecutive summers.The primary outcome was the change from baseline in the number of asthma exacerbations at 24 months.Secondary outcomes included severity of asthma exacerbation,asthma control test(ACT)score,percentage of forced expiratory volume in 1 s(FEV1)to the predicated value(FEV1%pred),peak expiratory flow(PEF),ratio of FEV1 to forced vital capacity(FEV1/FVC),and use of palliative drugs during bronchial asthma exacerbations at 12 and 24 months.The adverse events(AEs)were also assessed.RESULTS:A total of 835 patients with bronchial asthma were randomized in this trial.Compared with the placebo control,the PAT significantly decreased the mean number of asthma exacerbations(1.42;95%confidence interval,0.69 to 2.14;P<0.001),and increased the FEV1%pred at 24 months(P=0.039)and FEV1/FVC at 12 months(P=0.01)and 24 months(P=0.01).There were no significant differences between the groups in PEF or ACT score at 12 and 24 months,or in FEV1%pred at 12 months.Treatment-related AEs were mild and more common in the PAT group than in the placebo PAT group.No serious AEs were reported.CONCLUSION:PAT conducted on dog days could reduce asthma exacerbations in patients with bronchial asthma.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
In response to the challenges of inadequate predictive accuracy and limited generalization capability in data-driven modeling for the mechanical properties of the cold-rolled strip steel,a predictive modeling method n...In response to the challenges of inadequate predictive accuracy and limited generalization capability in data-driven modeling for the mechanical properties of the cold-rolled strip steel,a predictive modeling method named RFR-WOA is developed based on random forest regression(RFR)and whale optimization algorithm(WOA).Firstly,using Pearson and Spearman correlation analysis and Gini coefficient importance ranking on an actual production dataset containing 37,878 samples,22 key variables are selected as model inputs from 112 variables that affect mechanical properties.Subsequently,an RFR-based predictive model for the mechanical properties of cold-rolled strip steel is constructed.Then,with the combination of the coefficient of determination(R^(2))and root mean square error as the optimization objective,the hyperparameters of RFR model are iteratively optimized using WOA,and better predictive effectiveness is obtained.Finally,the mechanical properties prediction model based on RFR-WOA is compared with models established using deep neural networks,convolutional neural networks,and other methods.The test results on 9469 samples of actual production data show that the model developed present has better predictive accuracy and generalization capability.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 Xinjiang Normal University Outstanding Young Teacher Research Launch Fund Project(Grant No.XJNU202116)。
文摘We study a finite number of independent random walks with subexponentially distributed increments and negative drifts.We extend the one-dimensional results to finite and fully general stopping times.Assuming that the distribution of the lengths of these intervals is relatively light compared to the distribution of the increments of the random walks,we derive the asymptotic tail distribution of the partial maximum sum over the random time interval.
基金supported by the Natural Science Foundation of Hunan Province (2022JJ30987)the Key Research and Development Project of Hunan Province (2024JK2107),China。
文摘Objective:The incidence and mortality of colorectal carcinoma(CRC)continue to rise globally,highlighting the need to identify modifiable risk factors for early detection and prevention.Previous studies have demonstrated significant associations between CRC risk and various serum metabolites as well as inflammatory cytokines;however,due to limitations in study design and potential confounding factors,the causal relationships remain unclear.This study aims to investigate the causal relationships between inflammatory cytokines,serum metabolites,and CRC risk,providing a theoretical basis for the development of novel early diagnostic biomarkers and therapeutic targets.Methods:A two-sample Mendelian randomization(MR)design was applied using summary statistics from genome-wide association studies(GWAS).Instrumental variables(IVs)were derived from:1)metabolomics GWAS data of 1400 serum metabolites(n=8299);2)cytokine GWAS data of 91 inflammatory factors(n=14824);and 3)CRC risk data from the FinnGen consortium(6847 cases and 314193 controls).The primary analysis was conducted using the inverse-variance weighted(IVW)method,with sensitivity analyses performed using MR Egger regression and the weighted median method.Effect estimates including odds ratios(OR),95%confidence intervals(CI),and false discovery rates(FDR)were calculated.Results:MR analysis indicated that higher levels of axin-1(AXIN1)(OR=0.84195%CI 0.714 to 0.991)and Fms-related tyrosine kinase 3 ligand(Flt3L)(OR=0.916,95%CI 0.844 to 0.994)were associated with a reduced risk of CRC.In contrast,higher levels of Delta/Notchlike epidermal growth factor-related receptor(DNER)(OR=1.119,95%CI 1.009 to 1.241)and vascular endothelial growth factor A(VEGF-A)(OR=1.078,95%CI 1.011 to 1.150)were associated with an increased risk of CRC(all P<0.05).Metabolomics association analysis further identified 144 serum metabolites significantly correlated with these four key inflammatory cytokines(FDR<0.05),suggesting that they may regulate CRC risk through inflammatory pathways.Conclusion:Specific inflammatory cytokines and serum metabolites have causal relationships with the risk of CRC.These findings provide insights for further exploration of potential risk factors and the development of effective prevention strategies for CRC.
文摘The important work of Yu,et al.[1]who presented one of the first randomized controlled trials(RCTs)to directly compare robot-assisted and manual percutaneous coronary intervention(PCI),is commendable;offering important insights into the feasibility and outcomes of this emerging technology.While the analysis is timely,several issues warrant further consideration.
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.
文摘Although diet and gut microbial composition have been linked to chronic respiratory diseases,these associations remain difficult to interpret because of confounding and reverse causation.The gut-lung axis provides a plausible framework for this interaction,yet direct genetic evidence is limited.Using a two-step,two-sample Mendelian randomization(MR)framework,supplemented by multivariable MR(MVMR)to adjust for pleiotropic effects and Benjamini-Hochberg false discovery rate(FDR)correction for multiple testing,we assessed the causal contributions of dietary habits and gut microbial taxa to major chronic respiratory diseases.We identified 22 dietary factors with causal effects on disease risk and 225 microbial taxa that acted as independent risk or protective contributors.Mediation analyses further showed that the effects of 12 dietary habits were transmitted through 32 specific microbial taxa.Notably,genetically predicted pork intake increased the risk of chronic obstructive pulmonary disease(COPD)(OR=10.53,95%CI[8.54,13.00]),an effect partly mediated by elevated abundance of CAG-485 sp002404675.In contrast,bread consumption conferred protection against asthma(OR=0.68,95%CI[0.64,0.72]),whereas this benefit was offset by approximately 45%through a pathway involving reduced Veillonella abundance.Collectively,these findings provide genetic support for the gut-lung axis and demonstrate that the gut microbiome functions as a causal mediator linking diet to chronic respiratory disease risk.However,since this study was based on individuals of European ancestry,caution is warranted when generalizing these causal estimates to non-European populations,such as East Asian groups.This work suggests new opportunities for microbiota-targeted prevention and therapeutic strategies.
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.
基金supported by the National Key R&D Program of China under Grant No.2022YFA1003701the Open Research Fund of Yunnan Key Laboratory of Statistical Modeling and Data Analysis,Yunnan University under Grant No.SMDAYB2023004。
文摘Quantile regression(QR)has become an important tool to measure dependence of response variable's quantiles on a number of predictors for heterogeneous data,especially heavy-tailed data and outliers.However,it is quite challenging to make statistical inference on distributed high-dimensional QR with missing data due to the distributed nature,sparsity and missingness of data and nondifferentiable quantile loss function.To overcome the challenge,this paper develops a communicationefficient method to select variables and estimate parameters by utilizing a smooth function to approximate the non-differentiable quantile loss function and incorporating the idea of the inverse probability weighting and the penalty function.The proposed approach has three merits.First,it is both computationally and communicationally efficient because only the first-and second-order information of the approximate objective function are communicated at each iteration.Second,the proposed estimators possess the oracle property after a limited number of iterations without constraint on the number of machines.Third,the proposed method simultaneously selects variables and estimates parameters within a distributed framework,ensuring robustness to the specified response probability or propensity score function of the missing data mechanism.Simulation studies and a real example are used to illustrate the effectiveness of the proposed methodologies.
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.
基金supported by Qingdao Natural Science Foundation(No. 23-2-1-224-zyyd-jch)。
文摘Although the concentration of fine particulate matter(PM_(2.5))is reducing continuously,the proportion of secondary organic aerosols(SOA)in PM_(2.5) and the O_(3) levels are increasing.This is causing severe complex atmospheric pollution in North China.It is essential to identify and quantify the driving factors of SOA and O_(3),including the various pollution sources and meteorological factors.PM_(2.5) and volatile organic compounds(VOCs)samples were collected simultaneously in three cities in Shandong Province during different pollution scenarios from 2021 to 2023.Then,the carbonaceous aerosol and 99 VOC species were analyzed.Random forest(RF)combined with positive matrix factorization and an observation-based model(OBM)were used to quantify the key drivers of SOA and O_(3).Aromatic hydrocarbons were the main contributors to secondary organic aerosol potential(74.3%-89.9%),whereas alkenes contributed the most to the ozone formation potential(27.0%-62.3%).The RF modeling identified temperature and NOx as the dominant drivers of ozone formation.These accounted for 47.8%and 17.4%,respectively.Temperature showed a positive correlation with O_(3) because an increase in temperature can promote ozone formation.NOx had a significant negative correlation with O_(3),which was consistent with the conclusions from the sensitivity analysis of the OBM.The dominant contributors to SOA were vehicle emissions,solvent use,and industrial emissions.These accounted for 43.9%,18.2%,and 10.5%,respectively.An evident positive correlation existed between these emission sources and SOA.
基金Supported by“12th Five-year” National Science and Technology Pillar Program by the Ministry of Science and Technology of the People’s Republic of China:Clinical Evaluation and Technical Operation Specification Research on Preventing Bronchial Asthma Attacks by Acupoint Application in Winter Disease Summer Treatment(No. 2015BAI04B11)。
文摘OBJECTIVE:To assess the efficacy of point application therapy(PAT)in alleviating the exacerbation of chronic respiratory diseases represented by bronchial asthma.METHODS:In this multicenter randomized placebocontrolled trial,eligible bronchial asthma patients received placebo PAT on the dog days of the first summer to establish a baseline,and then patients who continued to participate in the trial and repassed the eligibility review were randomized to receive regular or placebo PAT in the next two consecutive summers.The primary outcome was the change from baseline in the number of asthma exacerbations at 24 months.Secondary outcomes included severity of asthma exacerbation,asthma control test(ACT)score,percentage of forced expiratory volume in 1 s(FEV1)to the predicated value(FEV1%pred),peak expiratory flow(PEF),ratio of FEV1 to forced vital capacity(FEV1/FVC),and use of palliative drugs during bronchial asthma exacerbations at 12 and 24 months.The adverse events(AEs)were also assessed.RESULTS:A total of 835 patients with bronchial asthma were randomized in this trial.Compared with the placebo control,the PAT significantly decreased the mean number of asthma exacerbations(1.42;95%confidence interval,0.69 to 2.14;P<0.001),and increased the FEV1%pred at 24 months(P=0.039)and FEV1/FVC at 12 months(P=0.01)and 24 months(P=0.01).There were no significant differences between the groups in PEF or ACT score at 12 and 24 months,or in FEV1%pred at 12 months.Treatment-related AEs were mild and more common in the PAT group than in the placebo PAT group.No serious AEs were reported.CONCLUSION:PAT conducted on dog days could reduce asthma exacerbations in patients with bronchial asthma.
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 National Natural Science Foundation of China(Grant 62573375)the Natural Science Foundation of Hebei Province(Grant F2024203038)+2 种基金the Science and Technology Research and Development Plan Project of Qinhuangdao City(Grant 202302B048)the Provincial Key Laboratory Performance Subsidy Project(Grant 22567612H)the Shandong Provincial Natural Science Foundation Youth Project(ZR2023QF044)。
文摘In response to the challenges of inadequate predictive accuracy and limited generalization capability in data-driven modeling for the mechanical properties of the cold-rolled strip steel,a predictive modeling method named RFR-WOA is developed based on random forest regression(RFR)and whale optimization algorithm(WOA).Firstly,using Pearson and Spearman correlation analysis and Gini coefficient importance ranking on an actual production dataset containing 37,878 samples,22 key variables are selected as model inputs from 112 variables that affect mechanical properties.Subsequently,an RFR-based predictive model for the mechanical properties of cold-rolled strip steel is constructed.Then,with the combination of the coefficient of determination(R^(2))and root mean square error as the optimization objective,the hyperparameters of RFR model are iteratively optimized using WOA,and better predictive effectiveness is obtained.Finally,the mechanical properties prediction model based on RFR-WOA is compared with models established using deep neural networks,convolutional neural networks,and other methods.The test results on 9469 samples of actual production data show that the model developed present has better predictive accuracy and generalization capability.
