Objective This study explored the potentially modifiable factors for depression and major depressive disorder(MDD)from the MR-Base database and further evaluated the associations between drug targets with MDD.Methods ...Objective This study explored the potentially modifiable factors for depression and major depressive disorder(MDD)from the MR-Base database and further evaluated the associations between drug targets with MDD.Methods We analyzed two-sample of Mendelian randomization(2SMR)using genetic variant depression(n=113,154)and MDD(n=208,811)from Genome-Wide Association Studies(GWAS).Separate calculations were performed with modifiable risk factors from MR-Base for 1,001 genomes.The MR analysis was performed by screening drug targets with MDD in the DrugBank database to explore the therapeutic targets for MDD.Inverse variance weighted(IVW),fixed-effect inverse variance weighted(FE-IVW),MR-Egger,weighted median,and weighted mode were used for complementary calculation.Results The potential causal relationship between modifiable risk factors and depression contained 459 results for depression and 424 for MDD.Also,the associations between drug targets and MDD showed that SLC6A4,GRIN2A,GRIN2C,SCN10A,and IL1B expression are associated with an increased risk of depression.In contrast,ADRB1,CHRNA3,HTR3A,GSTP1,and GABRG2 genes are candidate protective factors against depression.Conclusion This study identified the risk factors causally associated with depression and MDD,and estimated 10 drug targets with significant impact on MDD,providing essential information for formulating strategies to prevent and treat depression.展开更多
Objective:Chronic fatigue syndrome(CFS)is a prevalent symptom of post-coronavirus disease 2019(COVID-19)and is associated with unclear disease mechanisms.The herbal medicine Qingjin Yiqi granules(QJYQ)constitute a cli...Objective:Chronic fatigue syndrome(CFS)is a prevalent symptom of post-coronavirus disease 2019(COVID-19)and is associated with unclear disease mechanisms.The herbal medicine Qingjin Yiqi granules(QJYQ)constitute a clinically approved formula for treating post-COVID-19;however,its potential as a drug target for treating CFS remains largely unknown.This study aimed to identify novel causal factors for CFS and elucidate the potential targets and pharmacological mechanisms of action of QJYQ in treating CFS.Methods:This prospective cohort analysis included 4,212 adults aged≥65 years who were followed up for 7 years with 435 incident CFS cases.Causal modeling and multivariate logistic regression analysis were performed to identify the potential causal determinants of CFS.A proteome-wide,two-sample Mendelian randomization(MR)analysis was employed to explore the proteins associated with the identified causal factors of CFS,which may serve as potential drug targets.Furthermore,we performed a virtual screening analysis to assess the binding affinity between the bioactive compounds in QJYQ and CFS-associated proteins.Results:Among 4,212 participants(47.5%men)with a median age of 69 years(interquartile range:69–70 years)enrolled in 2004,435 developed CFS by 2011.Causal graph analysis with multivariate logistic regression identified frequent cough(odds ratio:1.74,95%confidence interval[CI]:1.15–2.63)and insomnia(odds ratio:2.59,95%CI:1.77–3.79)as novel causal factors of CFS.Proteome-wide MR analysis revealed that the upregulation of endothelial cell-selective adhesion molecule(ESAM)was causally linked to both chronic cough(odds ratio:1.019,95%CI:1.012–1.026,P=2.75 e^(−05))and insomnia(odds ratio:1.015,95%CI:1.008–1.022,P=4.40 e^(−08))in CFS.The major bioactive compounds of QJYQ,ginsenoside Rb2(docking score:−6.03)and RG4(docking score:−6.15),bound to ESAM with high affinity based on virtual screening.Conclusions:Our integrated analytical framework combining epidemiological,genetic,and in silico data provides a novel strategy for elucidating complex disease mechanisms,such as CFS,and informing models of action of traditional Chinese medicines,such as QJYQ.Further validation in animal models is warranted to confirm the potential pharmacological effects of QJYQ on ESAM and as a treatment for CFS.展开更多
Eavesdropping attacks have become one of the most common attacks on networks because of their easy implementation. Eavesdropping attacks not only lead to transmission data leakage but also develop into other more harm...Eavesdropping attacks have become one of the most common attacks on networks because of their easy implementation. Eavesdropping attacks not only lead to transmission data leakage but also develop into other more harmful attacks. Routing randomization is a relevant research direction for moving target defense, which has been proven to be an effective method to resist eavesdropping attacks. To counter eavesdropping attacks, in this study, we analyzed the existing routing randomization methods and found that their security and usability need to be further improved. According to the characteristics of eavesdropping attacks, which are “latent and transferable”, a routing randomization defense method based on deep reinforcement learning is proposed. The proposed method realizes routing randomization on packet-level granularity using programmable switches. To improve the security and quality of service of legitimate services in networks, we use the deep deterministic policy gradient to generate random routing schemes with support from powerful network state awareness. In-band network telemetry provides real-time, accurate, and comprehensive network state awareness for the proposed method. Various experiments show that compared with other typical routing randomization defense methods, the proposed method has obvious advantages in security and usability against eavesdropping attacks.展开更多
In the tracking problem for the maritime radiation source by a passive sensor,there are three main difficulties,i.e.,the poor observability of the radiation source,the detection uncertainty(false and missed detections...In the tracking problem for the maritime radiation source by a passive sensor,there are three main difficulties,i.e.,the poor observability of the radiation source,the detection uncertainty(false and missed detections)and the uncertainty of the target appearing/disappearing in the field of view.These difficulties can make the establishment or maintenance of the radiation source target track invalid.By incorporating the elevation information of the passive sensor into the automatic bearings-only tracking(BOT)and consolidating these uncertainties under the framework of random finite set(RFS),a novel approach for tracking maritime radiation source target with intermittent measurement was proposed.Under the RFS framework,the target state was represented as a set that can take on either an empty set or a singleton; meanwhile,the measurement uncertainty was modeled as a Bernoulli random finite set.Moreover,the elevation information of the sensor platform was introduced to ensure observability of passive measurements and obtain the unique target localization.Simulation experiments verify the validity of the proposed approach for tracking maritime radiation source and demonstrate the superiority of the proposed approach in comparison with the traditional integrated probabilistic data association(IPDA)method.The tracking performance under different conditions,particularly involving different existence probabilities and different appearance durations of the target,indicates that the method to solve our problem is robust and effective.展开更多
The paper studies stochastic dynamics of a two-degree-of-freedom system,where a primary linear system is connected to a nonlinear energy sink with cubic stiffness nonlinearity and viscous damping.While the primary mas...The paper studies stochastic dynamics of a two-degree-of-freedom system,where a primary linear system is connected to a nonlinear energy sink with cubic stiffness nonlinearity and viscous damping.While the primary mass is subjected to a zero-mean Gaussian white noise excitation,the main objective of this study is to maximise the efficiency of the targeted energy transfer in the system.A surrogate optimisation algorithm is proposed for this purpose and adopted for the stochastic framework.The optimisations are conducted separately for the nonlinear stiffness coefficient alone as well as for both the nonlinear stiffness and damping coefficients together.Three different optimisation cost functions,based on either energy of the system’s components or the dissipated energy,are considered.The results demonstrate some clear trends in values of the nonlinear energy sink coefficients and show the effect of different cost functions on the optimal values of the nonlinear system’s coefficients.展开更多
Background:Diabetic retinopathy(DR)urgently needs novel and effective therapeutic targets.Integrated analyses of plasma proteomic and genetic markers can clarify the causal relevance of proteins and discover novel tar...Background:Diabetic retinopathy(DR)urgently needs novel and effective therapeutic targets.Integrated analyses of plasma proteomic and genetic markers can clarify the causal relevance of proteins and discover novel targets for diseases,but no systematic screening for DR has been performed.Methods:Summary statistics of plasma protein quantitative trait loci(pQTL)were derived from two extensive genome-wide analysis study(GWAS)datasets and one systematic review,with over 100 thousand participants covering thousands of plasma proteins.DR data were sourced from the largest FinnGen study,comprising 10,413 DR cases and 308,633 European controls.Genetic instrumental variables were identified using multiple filters.In the two-sample MR analysis,Wald ratio and inverse variance-weighted(IVW)MR were utilized to investigate the causality of plasma proteins with DR.Bidirectional MR,Bayesian Co-localization,and phenotype scanning were employed to test for potential reverse causality and confounding factors in the main MR analyses.By systemically searching druggable gene lists,the ChEMBL database,DrugBank,and Gene Ontology database,the druggability and relevant functional pathways of the identified proteins were systematically evaluated.Results:Genetically predicted levels of 24 proteins were significantly associated with DR risk at a false discovery rate<0.05 including 11 with positive associations and 13 with negative associations.For each standard deviation increase in plasm protein levels,the odds ratios(ORs)for DR varied from 0.51(95%CI:0.36-0.73;P=2.22×10-5)for tubulin polymerization-promoting protein family member 3(TPPP3)to 2.02(95%CI:1.44-2.83;P=5.01×10-5)for olfactomedin like 3(OLFML3).Bidirectional MR indicated there was no reverse causality that interfered with the results of the main MR analyses.Four proteins exhibited strong co-localization evidence(PH4≥0.8):cytoplasmic tRNA synthetase(WARS),acrosin binding protein(ACRBP),and intercellular adhesion molecule 1(ICAM1)were negatively associated with DR risk,while neurogenic locus notch homolog protein 2(NOTCH2)showed a positive association.No confounding factors were detected between pQTLs and DR according to the phenotypic scan.Drugability assessments highlighted 6 proteins already in drug development endeavor and 18 novel drug targets,with metalloproteinase inhibitor 3(TIMP)currently in phase I clinical trials for DR.GO analysis identified 18 of 24 plasma proteins enriching 22 pathways related to cell differentiation and proliferation regulation.Conclusions:Twenty-four promising drug targets for DR were identified,including four plasma proteins with particular co-localization evidence.These findings offer new insights into DR's etiology and therapeutic targeting,exemplifying the value of genomic and proteomic data in drug target discovery.展开更多
基金supported by Natural Science Foundation of Shandong ProvinceChina[ZR2022MH115]the National Natural Science Foundation of China[81301479,82202593]。
文摘Objective This study explored the potentially modifiable factors for depression and major depressive disorder(MDD)from the MR-Base database and further evaluated the associations between drug targets with MDD.Methods We analyzed two-sample of Mendelian randomization(2SMR)using genetic variant depression(n=113,154)and MDD(n=208,811)from Genome-Wide Association Studies(GWAS).Separate calculations were performed with modifiable risk factors from MR-Base for 1,001 genomes.The MR analysis was performed by screening drug targets with MDD in the DrugBank database to explore the therapeutic targets for MDD.Inverse variance weighted(IVW),fixed-effect inverse variance weighted(FE-IVW),MR-Egger,weighted median,and weighted mode were used for complementary calculation.Results The potential causal relationship between modifiable risk factors and depression contained 459 results for depression and 424 for MDD.Also,the associations between drug targets and MDD showed that SLC6A4,GRIN2A,GRIN2C,SCN10A,and IL1B expression are associated with an increased risk of depression.In contrast,ADRB1,CHRNA3,HTR3A,GSTP1,and GABRG2 genes are candidate protective factors against depression.Conclusion This study identified the risk factors causally associated with depression and MDD,and estimated 10 drug targets with significant impact on MDD,providing essential information for formulating strategies to prevent and treat depression.
基金supported by an internal fund from Macao Polytechnic University(RP/FCSD-02/2022).
文摘Objective:Chronic fatigue syndrome(CFS)is a prevalent symptom of post-coronavirus disease 2019(COVID-19)and is associated with unclear disease mechanisms.The herbal medicine Qingjin Yiqi granules(QJYQ)constitute a clinically approved formula for treating post-COVID-19;however,its potential as a drug target for treating CFS remains largely unknown.This study aimed to identify novel causal factors for CFS and elucidate the potential targets and pharmacological mechanisms of action of QJYQ in treating CFS.Methods:This prospective cohort analysis included 4,212 adults aged≥65 years who were followed up for 7 years with 435 incident CFS cases.Causal modeling and multivariate logistic regression analysis were performed to identify the potential causal determinants of CFS.A proteome-wide,two-sample Mendelian randomization(MR)analysis was employed to explore the proteins associated with the identified causal factors of CFS,which may serve as potential drug targets.Furthermore,we performed a virtual screening analysis to assess the binding affinity between the bioactive compounds in QJYQ and CFS-associated proteins.Results:Among 4,212 participants(47.5%men)with a median age of 69 years(interquartile range:69–70 years)enrolled in 2004,435 developed CFS by 2011.Causal graph analysis with multivariate logistic regression identified frequent cough(odds ratio:1.74,95%confidence interval[CI]:1.15–2.63)and insomnia(odds ratio:2.59,95%CI:1.77–3.79)as novel causal factors of CFS.Proteome-wide MR analysis revealed that the upregulation of endothelial cell-selective adhesion molecule(ESAM)was causally linked to both chronic cough(odds ratio:1.019,95%CI:1.012–1.026,P=2.75 e^(−05))and insomnia(odds ratio:1.015,95%CI:1.008–1.022,P=4.40 e^(−08))in CFS.The major bioactive compounds of QJYQ,ginsenoside Rb2(docking score:−6.03)and RG4(docking score:−6.15),bound to ESAM with high affinity based on virtual screening.Conclusions:Our integrated analytical framework combining epidemiological,genetic,and in silico data provides a novel strategy for elucidating complex disease mechanisms,such as CFS,and informing models of action of traditional Chinese medicines,such as QJYQ.Further validation in animal models is warranted to confirm the potential pharmacological effects of QJYQ on ESAM and as a treatment for CFS.
文摘Eavesdropping attacks have become one of the most common attacks on networks because of their easy implementation. Eavesdropping attacks not only lead to transmission data leakage but also develop into other more harmful attacks. Routing randomization is a relevant research direction for moving target defense, which has been proven to be an effective method to resist eavesdropping attacks. To counter eavesdropping attacks, in this study, we analyzed the existing routing randomization methods and found that their security and usability need to be further improved. According to the characteristics of eavesdropping attacks, which are “latent and transferable”, a routing randomization defense method based on deep reinforcement learning is proposed. The proposed method realizes routing randomization on packet-level granularity using programmable switches. To improve the security and quality of service of legitimate services in networks, we use the deep deterministic policy gradient to generate random routing schemes with support from powerful network state awareness. In-band network telemetry provides real-time, accurate, and comprehensive network state awareness for the proposed method. Various experiments show that compared with other typical routing randomization defense methods, the proposed method has obvious advantages in security and usability against eavesdropping attacks.
基金Project(61101186)supported by the National Natural Science Foundation of China
文摘In the tracking problem for the maritime radiation source by a passive sensor,there are three main difficulties,i.e.,the poor observability of the radiation source,the detection uncertainty(false and missed detections)and the uncertainty of the target appearing/disappearing in the field of view.These difficulties can make the establishment or maintenance of the radiation source target track invalid.By incorporating the elevation information of the passive sensor into the automatic bearings-only tracking(BOT)and consolidating these uncertainties under the framework of random finite set(RFS),a novel approach for tracking maritime radiation source target with intermittent measurement was proposed.Under the RFS framework,the target state was represented as a set that can take on either an empty set or a singleton; meanwhile,the measurement uncertainty was modeled as a Bernoulli random finite set.Moreover,the elevation information of the sensor platform was introduced to ensure observability of passive measurements and obtain the unique target localization.Simulation experiments verify the validity of the proposed approach for tracking maritime radiation source and demonstrate the superiority of the proposed approach in comparison with the traditional integrated probabilistic data association(IPDA)method.The tracking performance under different conditions,particularly involving different existence probabilities and different appearance durations of the target,indicates that the method to solve our problem is robust and effective.
基金funding for this work from NSF-CMMI 2009270 and EPSRC EP/V034391/1.
文摘The paper studies stochastic dynamics of a two-degree-of-freedom system,where a primary linear system is connected to a nonlinear energy sink with cubic stiffness nonlinearity and viscous damping.While the primary mass is subjected to a zero-mean Gaussian white noise excitation,the main objective of this study is to maximise the efficiency of the targeted energy transfer in the system.A surrogate optimisation algorithm is proposed for this purpose and adopted for the stochastic framework.The optimisations are conducted separately for the nonlinear stiffness coefficient alone as well as for both the nonlinear stiffness and damping coefficients together.Three different optimisation cost functions,based on either energy of the system’s components or the dissipated energy,are considered.The results demonstrate some clear trends in values of the nonlinear energy sink coefficients and show the effect of different cost functions on the optimal values of the nonlinear system’s coefficients.
文摘针对动态武器目标分配(dynamic weapon target assignment,DWTA)问题,提出一种基于进化算法和局部搜索算法的文化基因算法(memetic algorithm,MA)。以最大化目标毁伤为目标,建立考虑能力约束、策略约束、资源约束、拦截可行性约束条件下的DWTA模型;引入虚拟排列进行编码以满足拦截可行性要求,设计将排列转化为实际分配方案的构造方法,给出算法运行过程中对随机事件的处理方法。通过与遗传算法(genetic algorithm,GA)、MA-GLS(memetic algorithm global local search)求解不同测试实例的对比仿真,结果表明,MA算法具有寻优速度快、优化能力强、稳定性好的优点。
基金funded by the Hainan Province Clinical Medical Center(82171084)the National Natural Science Foundation of China(82371086).
文摘Background:Diabetic retinopathy(DR)urgently needs novel and effective therapeutic targets.Integrated analyses of plasma proteomic and genetic markers can clarify the causal relevance of proteins and discover novel targets for diseases,but no systematic screening for DR has been performed.Methods:Summary statistics of plasma protein quantitative trait loci(pQTL)were derived from two extensive genome-wide analysis study(GWAS)datasets and one systematic review,with over 100 thousand participants covering thousands of plasma proteins.DR data were sourced from the largest FinnGen study,comprising 10,413 DR cases and 308,633 European controls.Genetic instrumental variables were identified using multiple filters.In the two-sample MR analysis,Wald ratio and inverse variance-weighted(IVW)MR were utilized to investigate the causality of plasma proteins with DR.Bidirectional MR,Bayesian Co-localization,and phenotype scanning were employed to test for potential reverse causality and confounding factors in the main MR analyses.By systemically searching druggable gene lists,the ChEMBL database,DrugBank,and Gene Ontology database,the druggability and relevant functional pathways of the identified proteins were systematically evaluated.Results:Genetically predicted levels of 24 proteins were significantly associated with DR risk at a false discovery rate<0.05 including 11 with positive associations and 13 with negative associations.For each standard deviation increase in plasm protein levels,the odds ratios(ORs)for DR varied from 0.51(95%CI:0.36-0.73;P=2.22×10-5)for tubulin polymerization-promoting protein family member 3(TPPP3)to 2.02(95%CI:1.44-2.83;P=5.01×10-5)for olfactomedin like 3(OLFML3).Bidirectional MR indicated there was no reverse causality that interfered with the results of the main MR analyses.Four proteins exhibited strong co-localization evidence(PH4≥0.8):cytoplasmic tRNA synthetase(WARS),acrosin binding protein(ACRBP),and intercellular adhesion molecule 1(ICAM1)were negatively associated with DR risk,while neurogenic locus notch homolog protein 2(NOTCH2)showed a positive association.No confounding factors were detected between pQTLs and DR according to the phenotypic scan.Drugability assessments highlighted 6 proteins already in drug development endeavor and 18 novel drug targets,with metalloproteinase inhibitor 3(TIMP)currently in phase I clinical trials for DR.GO analysis identified 18 of 24 plasma proteins enriching 22 pathways related to cell differentiation and proliferation regulation.Conclusions:Twenty-four promising drug targets for DR were identified,including four plasma proteins with particular co-localization evidence.These findings offer new insights into DR's etiology and therapeutic targeting,exemplifying the value of genomic and proteomic data in drug target discovery.