In this study,we investigate the ef-ficacy of a hybrid parallel algo-rithm aiming at enhancing the speed of evaluation of two-electron repulsion integrals(ERI)and Fock matrix generation on the Hygon C86/DCU(deep compu...In this study,we investigate the ef-ficacy of a hybrid parallel algo-rithm aiming at enhancing the speed of evaluation of two-electron repulsion integrals(ERI)and Fock matrix generation on the Hygon C86/DCU(deep computing unit)heterogeneous computing platform.Multiple hybrid parallel schemes are assessed using a range of model systems,including those with up to 1200 atoms and 10000 basis func-tions.The findings of our research reveal that,during Hartree-Fock(HF)calculations,a single DCU ex-hibits 33.6 speedups over 32 C86 CPU cores.Compared with the efficiency of Wuhan Electronic Structure Package on Intel X86 and NVIDIA A100 computing platform,the Hygon platform exhibits good cost-effective-ness,showing great potential in quantum chemistry calculation and other high-performance scientific computations.展开更多
针对触摸屏监控系统不能满足大中型立体仓库对数据进行存储和处理的功能需求,在Visual Studio 2019集成开发环境中,采用C#语言开发一套立体仓库上位机控制系统。以多线程的方式实时读取库位信息;以S7-1200 PLC作为主控制器,设计产品的...针对触摸屏监控系统不能满足大中型立体仓库对数据进行存储和处理的功能需求,在Visual Studio 2019集成开发环境中,采用C#语言开发一套立体仓库上位机控制系统。以多线程的方式实时读取库位信息;以S7-1200 PLC作为主控制器,设计产品的自动入库和自动出库程序流程,采用SCL语言设计了库位先进先出的控制程序。C#和S7-1200 PLC之间采用S7通信的方式控制立体仓库的出入库操作和库位信息采集,3年的现场运行情况表明,整个系统能在上位机上对立体仓库进行手动控制和自动控制,能精确快速地进行入库出库操作,运行平稳,上位机上能正确实时显示库位信息,达到了预期的结果。展开更多
The S38C railway axle undergoes induction hardening,resulting in a gradient-distributed microstructure and mechanical properties.The accurate identification of gradient-distributed plastic parameters for the S38C axle...The S38C railway axle undergoes induction hardening,resulting in a gradient-distributed microstructure and mechanical properties.The accurate identification of gradient-distributed plastic parameters for the S38C axle remains a challenging task.To tackle this challenge,the present study proposes a novel approach for identifying the gradient-distributed plastic parameters for the S38C axle by integrating nano-indentation techniques with the machine learning method.Firstly,nano-indentation tests are conducted along the radial direction of the S38C axle to obtain the gradient-distributed load-displacement curves,nano-hardness,and elastic modulus.Subsequently,the dimensionless analysis is performed to obtain the representative stress,strain,and yield stress from load-displacement curves.These parameters are then incorporated into the machine learning method as physical information to identify the gradient-distributed plastic parameters of the S38C axle.The results indicate that the proposed method based on the physics-informed neural network and multi-fidelity neural network successfully identifies the gradient-distributed plastic parameters of the S38C axles and demonstrates superior prediction accuracy and generalization compared with the purely data-driven machine learning method.展开更多
BACKGROUND Mucosal healing(MH)is the major therapeutic target for Crohn's disease(CD).As the most commonly involved intestinal segment,small bowel(SB)assessment is crucial for CD patients.Yet,it poses a significan...BACKGROUND Mucosal healing(MH)is the major therapeutic target for Crohn's disease(CD).As the most commonly involved intestinal segment,small bowel(SB)assessment is crucial for CD patients.Yet,it poses a significant challenge due to its limited accessibility through conventional endoscopic methods.AIM To establish a noninvasive radiomic model based on computed tomography enterography(CTE)for MH assessment in SBCD patients.METHODS Seventy-three patients diagnosed with SBCD were included and divided into a training cohort(n=55)and a test cohort(n=18).Radiomic features were obtained from CTE images to establish a radiomic model.Patient demographics were analysed to establish a clinical model.A radiomic-clinical nomogram was constructed by combining significant clinical and radiomic features.The diagnostic efficacy and clinical benefit were evaluated via receiver operating characteristic(ROC)curve analysis and decision curve analysis(DCA),respectively.RESULTS Of the 73 patients enrolled,25 patients achieved MH.The radiomic-clinical nomogram had an area under the ROC curve of 0.961(95%confidence interval:0.886-1.000)in the training cohort and 0.958(0.877-1.000)in the test cohort and provided superior clinical benefit to either the clinical or radiomic models alone,as demonstrated by DCA.CONCLUSION These results indicate that the CTE-based radiomic-clinical nomogram is a promising imaging biomarker for MH and serves as a potential noninvasive alternative to enteroscopy for MH assessment in SBCD patients.展开更多
Alzheimer’s disease is initially thought to be caused by age-associated accumulation of plaques,in recent years,research has increasingly associated Alzheimer’s disease with lysosomal storage and metabolic disorders...Alzheimer’s disease is initially thought to be caused by age-associated accumulation of plaques,in recent years,research has increasingly associated Alzheimer’s disease with lysosomal storage and metabolic disorders,and the explanation of its pathogenesis has shifted from amyloid and tau accumulation to oxidative stress and impaired lipid and glucose metabolism aggravated by hypoxic conditions.However,the underlying mechanisms linking those cellular processes and conditions to disease progression have yet to be defined.Here,we applied a disease similarity approach to identify unknown molecular targets of Alzheimer’s disease by using transcriptomic data from congenital diseases known to increase Alzheimer’s disease risk,namely Down syndrome,Niemann-Pick type C disease,and mucopolysaccharidoses I.We uncovered common pathways,hub genes,and miRNAs across in vitro and in vivo models of these diseases as potential molecular targets for neuroprotection and amelioration of Alzheimer’s disease pathology,many of which have never been associated with Alzheimer’s disease.We then investigated common molecular alterations in brain samples from a Niemann-Pick type C disease mouse model by juxtaposing them with brain samples of both human and mouse models of Alzheimer’s disease.Detailed phenotypic,molecular,chronological,and biological aging analyses revealed that the Npc1tm(I1061T)Dso mouse model can serve as a potential short-lived in vivo model for brain aging and Alzheimer’s disease research.This research represents the first comprehensive approach to congenital disease association with neurodegeneration and a new perspective on Alzheimer’s disease research while highlighting shortcomings and lack of correlation in diverse in vitro models.Considering the lack of an Alzheimer’s disease mouse model that recapitulates the physiological hallmarks of brain aging,the short-lived Npc1^(tm(I1061T)Dso) mouse model can further accelerate the research in these fields and offer a unique model for understanding the molecular mechanisms of Alzheimer’s disease from a perspective of accelerated brain aging.展开更多
Hepatitis C virus(HCV)and hepatitis B virus(HBV)infections are increasingly recognized as significant etiological factors in the pathogenesis of B-cell non-Hodgkin’s lymphomas(B-NHLs).Epidemiological and molecular st...Hepatitis C virus(HCV)and hepatitis B virus(HBV)infections are increasingly recognized as significant etiological factors in the pathogenesis of B-cell non-Hodgkin’s lymphomas(B-NHLs).Epidemiological and molecular studies have demonstrated a consistent association between chronic viral infection and B-NHLs.Multiple pathogenic mechanisms have been implicated in lymphomagenesis,both direct and indirect,including chronic antigenic stimulation,direct infection of B cells,and viral protein-mediated oncogenic signaling,It is likely that a combination of several pathogenic conditions is required to eventually lead to the development of lymphoma.The prevalence of B-cell lymphomas among individuals with chronic HCV or HBV infection presents a complex pathogenetic scenario,given the tumor heterogeneity and variable clinical behavior,and poses therapeutic challenges,due to the partial efficacy of current treatment options.The advent of direct-acting antivirals(DAAs)for HCV and high-genetic barrier nucleos(t)ide analogues(NAs)for HBV has improved patient outcomes.In indolent HCV-associated B-NHLs,antiviral therapy with DAAs alone often achieves sustained virologic response and may lead to lymphoma regression.Conversely,aggressive subtypes like diffuse large B-cell lymphomas require combination treatment with immunochemotherapy.In the setting of HBV-associated lymphomas,antiviral prophylaxis with potent NAs(e.g.,entecavir or tenofovir)is essential to prevent HBV reactivation during rituximab-containing chemotherapy regimen.The integration of antiviral and anticancer therapies has been shown to enhance survival outcomes while mitigating hepatic toxicity.A comprehensive understanding of the biological interplay between chronic viral infection and B-cell transformation is critical for optimizing diagnostic and therapeutic strategies.Aim of this viewpoint is to provide evidence that early viral detection and prompt management remain the most effective strategies to improve survival rates and to reduce treatment-related morbidity in these patients.展开更多
BACKGROUND Visceral adipose tissue(VAT)plays a role in the pathogenesis of Crohn's disease(CD)and is associated with treatment outcomes following infliximab(IFX)therapy.We developed and validated the first delta-r...BACKGROUND Visceral adipose tissue(VAT)plays a role in the pathogenesis of Crohn's disease(CD)and is associated with treatment outcomes following infliximab(IFX)therapy.We developed and validated the first delta-radiomics model to quantify VAT heterogeneity as a predictive biomarker for IFX response in patients with CD.AIM To develop a longitudinal computed tomography(CT)-based delta-radiomics model of VAT for predicting secondary loss of response(SLR)in patients with CD.METHODS This retrospective study included 161 patients with CD who achieved clinical remission following IFX induction therapy between 2015 and 2023.All patients underwent CT enterography before IFX initiation and after completing induction therapy.VAT volume was delineated by two radiologists in consensus.Radiomics features were extracted from pre-treatment and post-induction CT images,and delta-radiomics features were calculated as follows:Delta features=Feature-post-Feature-pre.A radiomics model was constructed using logistic regression.Model performance was assessed using discrimination,calibration,and decision curve analyses.RESULTS Nine significant delta-radiomics features were used to develop the delta-radiomics model,yielding an area under the receiver operating characteristic curve(AUC)of 0.816(95%CI:0.737-0.896)in the training cohort and 0.750(95%CI:0.605-0.895)in the validation cohort.Multivariable logistic regression identified platelet count,Montreal behavior classification,and the VAT/subcutaneous adipose tissue volume ratio prior to treatment as independent risk factors for SLR.The combined model integrating clinical predictors and delta-radiomics features achieved superior predictive performance,with an AUC of 0.853(95%CI:0.786-0.921)in the training cohort and 0.812(95%CI:0.677-0.948)in the validation cohort.CONCLUSION We developed a predictive model based on longitudinal changes in VAT,demonstrating significant potential for identifying patients with CD at high risk of SLR to IFX therapy.展开更多
Based on BERTopic Model,the paper combines qualitative and quantitative methods to explore the reception of Can Xue’s translated works by analyzing readers’book reviews posted on Goodreads and Lovereading.We first c...Based on BERTopic Model,the paper combines qualitative and quantitative methods to explore the reception of Can Xue’s translated works by analyzing readers’book reviews posted on Goodreads and Lovereading.We first collected book reviews from these two well-known websites by Python.Through topic analysis of these reviews,we identified recurring topics,including details of her translated works and appreciation of their translation quality.Then,employing sentiment and content analysis methods,the paper explored the emotional attitudes and the specific thoughts of readers toward Can Xue and her translated works.The fingdings revealed that,among the 408 reviews,though the reception of Can Xue’s translated works was relatively positive,the current level of attention and recognition remains insufficient.However,based on the research results,the paper can derive valuable insights into the translation and dissemination processes such as adjusting translation and dissemination strategies,so that the global reach of Chinese literature and culture can be better facilitated.展开更多
Food allergy has become a global concern.Spleen tyrosine kinase(SYK)inhibitors are promising therapeutics against allergic disorders.In this study,a total of 300 natural phenolic compounds were firstly subjected to vi...Food allergy has become a global concern.Spleen tyrosine kinase(SYK)inhibitors are promising therapeutics against allergic disorders.In this study,a total of 300 natural phenolic compounds were firstly subjected to virtual screening.Sesamin and its metabolites,sesamin monocatechol(SC-1)and sesamin dicatechol(SC-2),were identified as potential SYK inhibitors,showing high binding affinity and inhibition efficiency towards SYK.Compared with R406(a traditional SYK inhibitor),sesamin,SC-1,and SC-2 had lower binding energy and inhibition constant(Ki)during molecular docking,exhibited higher bioavailability,safety,metabolism/clearance rate,and distribution uniformity ADMET predictions,and showed high stability in occupying the ATP-binding pocket of SYK during molecular dynamics simulations.In anti-dinitrophenyl-immunoglobulin E(Anti-DNP-Ig E)/dinitrophenyl-human serum albumin(DNP-HSA)-stimulated rat basophilic leukemia(RBL-2H3)cells,sesamin in the concentration range of 5-80μmol/L influenced significantly the degranulation and cytokine release,with 54.00%inhibition againstβ-hexosaminidase release and 58.45%decrease in histamine.In BALB/c mice,sesamin could ameliorate Anti-DNP-Ig E/DNP-HSA-induced passive cutaneous anaphylaxis(PCA)and ovalbumin(OVA)-induced active systemic anaphylaxis(ASA)reactions,reduce the levels of allergic mediators(immunoglobulins and pro-inflammatory cytokines),partially correct the imbalance of T helper(Th)cells differentiation in the spleen,and inhibit the phosphorylation of SYK and its downstream signaling proteins,including p38 mitogen-activated protein kinases(p38 MAPK),extracellular signalregulated kinases(ERK),and p65 nuclear factor-κB(p65 NF-κB)in the spleen.Thus,sesamin may be a safe and versatile SYK inhibitor that can alleviate Ig E-mediated food allergies.展开更多
This study investigates the transmission dynamics of conjunctivitis using stochastic delay differential equations(SDDEs).A delayed stochastic model is formulated by dividing the population into five distinct compartme...This study investigates the transmission dynamics of conjunctivitis using stochastic delay differential equations(SDDEs).A delayed stochastic model is formulated by dividing the population into five distinct compartments:susceptible,exposed,infected,environmental irritants,and recovered individuals.The model undergoes thorough analytical examination,addressing key dynamical properties including positivity,boundedness,existence,and uniqueness of solutions.Local and global stability around the equilibrium points is studied with respect to the basic reproduction number.The existence of a unique global positive solution for the stochastic delayed model is established.In addition,a stochastic nonstandard finite difference scheme is developed,which is shown to be dynamically consistent and convergent toward the equilibrium states.The scheme preserves the essential qualitative features of the model and demonstrates improved performance when compared to existing numerical methods.Finally,the impact of time delays and stochastic fluctuations on the susceptible and infected populations is analyzed.展开更多
In recent years,the exponential proliferation of smart devices with their intelligent applications poses severe challenges on conventional cellular networks.Such challenges can be potentially overcome by integrating c...In recent years,the exponential proliferation of smart devices with their intelligent applications poses severe challenges on conventional cellular networks.Such challenges can be potentially overcome by integrating communication,computing,caching,and control(i4C)technologies.In this survey,we first give a snapshot of different aspects of the i4C,comprising background,motivation,leading technological enablers,potential applications,and use cases.Next,we describe different models of communication,computing,caching,and control(4C)to lay the foundation of the integration approach.We review current stateof-the-art research efforts related to the i4C,focusing on recent trends of both conventional and artificial intelligence(AI)-based integration approaches.We also highlight the need for intelligence in resources integration.Then,we discuss the integration of sensing and communication(ISAC)and classify the integration approaches into various classes.Finally,we propose open challenges and present future research directions for beyond 5G networks,such as 6G.展开更多
Cloud storage is widely used by large companies to store vast amounts of data and files,offering flexibility,financial savings,and security.However,information shoplifting poses significant threats,potentially leading...Cloud storage is widely used by large companies to store vast amounts of data and files,offering flexibility,financial savings,and security.However,information shoplifting poses significant threats,potentially leading to poor performance and privacy breaches.Blockchain-based cognitive computing can help protect and maintain information security and privacy in cloud platforms,ensuring businesses can focus on business development.To ensure data security in cloud platforms,this research proposed a blockchain-based Hybridized Data Driven Cognitive Computing(HD2C)model.However,the proposed HD2C framework addresses breaches of the privacy information of mixed participants of the Internet of Things(IoT)in the cloud.HD2C is developed by combining Federated Learning(FL)with a Blockchain consensus algorithm to connect smart contracts with Proof of Authority.The“Data Island”problem can be solved by FL’s emphasis on privacy and lightning-fast processing,while Blockchain provides a decentralized incentive structure that is impervious to poisoning.FL with Blockchain allows quick consensus through smart member selection and verification.The HD2C paradigm significantly improves the computational processing efficiency of intelligent manufacturing.Extensive analysis results derived from IIoT datasets confirm HD2C superiority.When compared to other consensus algorithms,the Blockchain PoA’s foundational cost is significant.The accuracy and memory utilization evaluation results predict the total benefits of the system.In comparison to the values 0.004 and 0.04,the value of 0.4 achieves good accuracy.According to the experiment results,the number of transactions per second has minimal impact on memory requirements.The findings of this study resulted in the development of a brand-new IIoT framework based on blockchain technology.展开更多
基金supported by the National Natural Science Foundation of China(No.22373112 to Ji Qi,No.22373111 and 21921004 to Minghui Yang)GH-fund A(No.202107011790)。
文摘In this study,we investigate the ef-ficacy of a hybrid parallel algo-rithm aiming at enhancing the speed of evaluation of two-electron repulsion integrals(ERI)and Fock matrix generation on the Hygon C86/DCU(deep computing unit)heterogeneous computing platform.Multiple hybrid parallel schemes are assessed using a range of model systems,including those with up to 1200 atoms and 10000 basis func-tions.The findings of our research reveal that,during Hartree-Fock(HF)calculations,a single DCU ex-hibits 33.6 speedups over 32 C86 CPU cores.Compared with the efficiency of Wuhan Electronic Structure Package on Intel X86 and NVIDIA A100 computing platform,the Hygon platform exhibits good cost-effective-ness,showing great potential in quantum chemistry calculation and other high-performance scientific computations.
文摘针对触摸屏监控系统不能满足大中型立体仓库对数据进行存储和处理的功能需求,在Visual Studio 2019集成开发环境中,采用C#语言开发一套立体仓库上位机控制系统。以多线程的方式实时读取库位信息;以S7-1200 PLC作为主控制器,设计产品的自动入库和自动出库程序流程,采用SCL语言设计了库位先进先出的控制程序。C#和S7-1200 PLC之间采用S7通信的方式控制立体仓库的出入库操作和库位信息采集,3年的现场运行情况表明,整个系统能在上位机上对立体仓库进行手动控制和自动控制,能精确快速地进行入库出库操作,运行平稳,上位机上能正确实时显示库位信息,达到了预期的结果。
基金supported by the National Key Research and Development Plan(Grant No.2022YFB3401901)the National Natural Science Foundation of China(Grant Nos.12192210,12192214,12072295,and 12222209)+1 种基金Independent Project of State Key Laboratory of Rail Transit Vehicle System(Grant No.2023TPL-T03)Fundamental Research Funds for the Central Universities(Grant No.2682023CG004).
文摘The S38C railway axle undergoes induction hardening,resulting in a gradient-distributed microstructure and mechanical properties.The accurate identification of gradient-distributed plastic parameters for the S38C axle remains a challenging task.To tackle this challenge,the present study proposes a novel approach for identifying the gradient-distributed plastic parameters for the S38C axle by integrating nano-indentation techniques with the machine learning method.Firstly,nano-indentation tests are conducted along the radial direction of the S38C axle to obtain the gradient-distributed load-displacement curves,nano-hardness,and elastic modulus.Subsequently,the dimensionless analysis is performed to obtain the representative stress,strain,and yield stress from load-displacement curves.These parameters are then incorporated into the machine learning method as physical information to identify the gradient-distributed plastic parameters of the S38C axle.The results indicate that the proposed method based on the physics-informed neural network and multi-fidelity neural network successfully identifies the gradient-distributed plastic parameters of the S38C axles and demonstrates superior prediction accuracy and generalization compared with the purely data-driven machine learning method.
基金Supported by Natural Science Foundation of Anhui Medical University,No.2023xkj130.
文摘BACKGROUND Mucosal healing(MH)is the major therapeutic target for Crohn's disease(CD).As the most commonly involved intestinal segment,small bowel(SB)assessment is crucial for CD patients.Yet,it poses a significant challenge due to its limited accessibility through conventional endoscopic methods.AIM To establish a noninvasive radiomic model based on computed tomography enterography(CTE)for MH assessment in SBCD patients.METHODS Seventy-three patients diagnosed with SBCD were included and divided into a training cohort(n=55)and a test cohort(n=18).Radiomic features were obtained from CTE images to establish a radiomic model.Patient demographics were analysed to establish a clinical model.A radiomic-clinical nomogram was constructed by combining significant clinical and radiomic features.The diagnostic efficacy and clinical benefit were evaluated via receiver operating characteristic(ROC)curve analysis and decision curve analysis(DCA),respectively.RESULTS Of the 73 patients enrolled,25 patients achieved MH.The radiomic-clinical nomogram had an area under the ROC curve of 0.961(95%confidence interval:0.886-1.000)in the training cohort and 0.958(0.877-1.000)in the test cohort and provided superior clinical benefit to either the clinical or radiomic models alone,as demonstrated by DCA.CONCLUSION These results indicate that the CTE-based radiomic-clinical nomogram is a promising imaging biomarker for MH and serves as a potential noninvasive alternative to enteroscopy for MH assessment in SBCD patients.
基金supported by the NIA/NIH(1K01AG060040).Studies performed by JN were funded by the NICHD/NIH(5R00HD096117)Microscopy Core Facility supported,in part,with funding from NIH-NCI Cancer Center Support Grant P30 CA016059.
文摘Alzheimer’s disease is initially thought to be caused by age-associated accumulation of plaques,in recent years,research has increasingly associated Alzheimer’s disease with lysosomal storage and metabolic disorders,and the explanation of its pathogenesis has shifted from amyloid and tau accumulation to oxidative stress and impaired lipid and glucose metabolism aggravated by hypoxic conditions.However,the underlying mechanisms linking those cellular processes and conditions to disease progression have yet to be defined.Here,we applied a disease similarity approach to identify unknown molecular targets of Alzheimer’s disease by using transcriptomic data from congenital diseases known to increase Alzheimer’s disease risk,namely Down syndrome,Niemann-Pick type C disease,and mucopolysaccharidoses I.We uncovered common pathways,hub genes,and miRNAs across in vitro and in vivo models of these diseases as potential molecular targets for neuroprotection and amelioration of Alzheimer’s disease pathology,many of which have never been associated with Alzheimer’s disease.We then investigated common molecular alterations in brain samples from a Niemann-Pick type C disease mouse model by juxtaposing them with brain samples of both human and mouse models of Alzheimer’s disease.Detailed phenotypic,molecular,chronological,and biological aging analyses revealed that the Npc1tm(I1061T)Dso mouse model can serve as a potential short-lived in vivo model for brain aging and Alzheimer’s disease research.This research represents the first comprehensive approach to congenital disease association with neurodegeneration and a new perspective on Alzheimer’s disease research while highlighting shortcomings and lack of correlation in diverse in vitro models.Considering the lack of an Alzheimer’s disease mouse model that recapitulates the physiological hallmarks of brain aging,the short-lived Npc1^(tm(I1061T)Dso) mouse model can further accelerate the research in these fields and offer a unique model for understanding the molecular mechanisms of Alzheimer’s disease from a perspective of accelerated brain aging.
基金supported by the National Italian Research Council(CNR)“Progetto DSB.AD007.305.001”to Monica Rinaldi。
文摘Hepatitis C virus(HCV)and hepatitis B virus(HBV)infections are increasingly recognized as significant etiological factors in the pathogenesis of B-cell non-Hodgkin’s lymphomas(B-NHLs).Epidemiological and molecular studies have demonstrated a consistent association between chronic viral infection and B-NHLs.Multiple pathogenic mechanisms have been implicated in lymphomagenesis,both direct and indirect,including chronic antigenic stimulation,direct infection of B cells,and viral protein-mediated oncogenic signaling,It is likely that a combination of several pathogenic conditions is required to eventually lead to the development of lymphoma.The prevalence of B-cell lymphomas among individuals with chronic HCV or HBV infection presents a complex pathogenetic scenario,given the tumor heterogeneity and variable clinical behavior,and poses therapeutic challenges,due to the partial efficacy of current treatment options.The advent of direct-acting antivirals(DAAs)for HCV and high-genetic barrier nucleos(t)ide analogues(NAs)for HBV has improved patient outcomes.In indolent HCV-associated B-NHLs,antiviral therapy with DAAs alone often achieves sustained virologic response and may lead to lymphoma regression.Conversely,aggressive subtypes like diffuse large B-cell lymphomas require combination treatment with immunochemotherapy.In the setting of HBV-associated lymphomas,antiviral prophylaxis with potent NAs(e.g.,entecavir or tenofovir)is essential to prevent HBV reactivation during rituximab-containing chemotherapy regimen.The integration of antiviral and anticancer therapies has been shown to enhance survival outcomes while mitigating hepatic toxicity.A comprehensive understanding of the biological interplay between chronic viral infection and B-cell transformation is critical for optimizing diagnostic and therapeutic strategies.Aim of this viewpoint is to provide evidence that early viral detection and prompt management remain the most effective strategies to improve survival rates and to reduce treatment-related morbidity in these patients.
基金Supported by the National Natural Science Foundation of China,No.82372072 and No.82071986.
文摘BACKGROUND Visceral adipose tissue(VAT)plays a role in the pathogenesis of Crohn's disease(CD)and is associated with treatment outcomes following infliximab(IFX)therapy.We developed and validated the first delta-radiomics model to quantify VAT heterogeneity as a predictive biomarker for IFX response in patients with CD.AIM To develop a longitudinal computed tomography(CT)-based delta-radiomics model of VAT for predicting secondary loss of response(SLR)in patients with CD.METHODS This retrospective study included 161 patients with CD who achieved clinical remission following IFX induction therapy between 2015 and 2023.All patients underwent CT enterography before IFX initiation and after completing induction therapy.VAT volume was delineated by two radiologists in consensus.Radiomics features were extracted from pre-treatment and post-induction CT images,and delta-radiomics features were calculated as follows:Delta features=Feature-post-Feature-pre.A radiomics model was constructed using logistic regression.Model performance was assessed using discrimination,calibration,and decision curve analyses.RESULTS Nine significant delta-radiomics features were used to develop the delta-radiomics model,yielding an area under the receiver operating characteristic curve(AUC)of 0.816(95%CI:0.737-0.896)in the training cohort and 0.750(95%CI:0.605-0.895)in the validation cohort.Multivariable logistic regression identified platelet count,Montreal behavior classification,and the VAT/subcutaneous adipose tissue volume ratio prior to treatment as independent risk factors for SLR.The combined model integrating clinical predictors and delta-radiomics features achieved superior predictive performance,with an AUC of 0.853(95%CI:0.786-0.921)in the training cohort and 0.812(95%CI:0.677-0.948)in the validation cohort.CONCLUSION We developed a predictive model based on longitudinal changes in VAT,demonstrating significant potential for identifying patients with CD at high risk of SLR to IFX therapy.
基金supported by the 2023 Youth Fund for Humanities and Social Sciences Research by the Ministry of Education of the People’s Republic of China(Grant No.23YJC740004).
文摘Based on BERTopic Model,the paper combines qualitative and quantitative methods to explore the reception of Can Xue’s translated works by analyzing readers’book reviews posted on Goodreads and Lovereading.We first collected book reviews from these two well-known websites by Python.Through topic analysis of these reviews,we identified recurring topics,including details of her translated works and appreciation of their translation quality.Then,employing sentiment and content analysis methods,the paper explored the emotional attitudes and the specific thoughts of readers toward Can Xue and her translated works.The fingdings revealed that,among the 408 reviews,though the reception of Can Xue’s translated works was relatively positive,the current level of attention and recognition remains insufficient.However,based on the research results,the paper can derive valuable insights into the translation and dissemination processes such as adjusting translation and dissemination strategies,so that the global reach of Chinese literature and culture can be better facilitated.
基金Incubation Program of Youth Innovation in Shandong ProvinceKey Research and Development Program of Shandong Province(2021TZXD007)。
文摘Food allergy has become a global concern.Spleen tyrosine kinase(SYK)inhibitors are promising therapeutics against allergic disorders.In this study,a total of 300 natural phenolic compounds were firstly subjected to virtual screening.Sesamin and its metabolites,sesamin monocatechol(SC-1)and sesamin dicatechol(SC-2),were identified as potential SYK inhibitors,showing high binding affinity and inhibition efficiency towards SYK.Compared with R406(a traditional SYK inhibitor),sesamin,SC-1,and SC-2 had lower binding energy and inhibition constant(Ki)during molecular docking,exhibited higher bioavailability,safety,metabolism/clearance rate,and distribution uniformity ADMET predictions,and showed high stability in occupying the ATP-binding pocket of SYK during molecular dynamics simulations.In anti-dinitrophenyl-immunoglobulin E(Anti-DNP-Ig E)/dinitrophenyl-human serum albumin(DNP-HSA)-stimulated rat basophilic leukemia(RBL-2H3)cells,sesamin in the concentration range of 5-80μmol/L influenced significantly the degranulation and cytokine release,with 54.00%inhibition againstβ-hexosaminidase release and 58.45%decrease in histamine.In BALB/c mice,sesamin could ameliorate Anti-DNP-Ig E/DNP-HSA-induced passive cutaneous anaphylaxis(PCA)and ovalbumin(OVA)-induced active systemic anaphylaxis(ASA)reactions,reduce the levels of allergic mediators(immunoglobulins and pro-inflammatory cytokines),partially correct the imbalance of T helper(Th)cells differentiation in the spleen,and inhibit the phosphorylation of SYK and its downstream signaling proteins,including p38 mitogen-activated protein kinases(p38 MAPK),extracellular signalregulated kinases(ERK),and p65 nuclear factor-κB(p65 NF-κB)in the spleen.Thus,sesamin may be a safe and versatile SYK inhibitor that can alleviate Ig E-mediated food allergies.
基金supported by Princess Nourah bint Abdulrahman University Researchers Supporting Project number(PNURSP2025R899)Princess Nourah bint Abdulrahman University,Riyadh,Saudi Arabiasupported by the Deanship of Scientific Research,Vice Presidency for Graduate Studies and Scientific Research,King Faisal University,Saudi Arabia(KFU252831)。
文摘This study investigates the transmission dynamics of conjunctivitis using stochastic delay differential equations(SDDEs).A delayed stochastic model is formulated by dividing the population into five distinct compartments:susceptible,exposed,infected,environmental irritants,and recovered individuals.The model undergoes thorough analytical examination,addressing key dynamical properties including positivity,boundedness,existence,and uniqueness of solutions.Local and global stability around the equilibrium points is studied with respect to the basic reproduction number.The existence of a unique global positive solution for the stochastic delayed model is established.In addition,a stochastic nonstandard finite difference scheme is developed,which is shown to be dynamically consistent and convergent toward the equilibrium states.The scheme preserves the essential qualitative features of the model and demonstrates improved performance when compared to existing numerical methods.Finally,the impact of time delays and stochastic fluctuations on the susceptible and infected populations is analyzed.
基金supported in part by National Key R&D Program of China(2019YFE0196400)Key Research and Development Program of Shaanxi(2022KWZ09)+4 种基金National Natural Science Foundation of China(61771358,61901317,62071352)Fundamental Research Funds for the Central Universities(JB190104)Joint Education Project between China and Central-Eastern European Countries(202005)the 111 Project(B08038)。
文摘In recent years,the exponential proliferation of smart devices with their intelligent applications poses severe challenges on conventional cellular networks.Such challenges can be potentially overcome by integrating communication,computing,caching,and control(i4C)technologies.In this survey,we first give a snapshot of different aspects of the i4C,comprising background,motivation,leading technological enablers,potential applications,and use cases.Next,we describe different models of communication,computing,caching,and control(4C)to lay the foundation of the integration approach.We review current stateof-the-art research efforts related to the i4C,focusing on recent trends of both conventional and artificial intelligence(AI)-based integration approaches.We also highlight the need for intelligence in resources integration.Then,we discuss the integration of sensing and communication(ISAC)and classify the integration approaches into various classes.Finally,we propose open challenges and present future research directions for beyond 5G networks,such as 6G.
文摘Cloud storage is widely used by large companies to store vast amounts of data and files,offering flexibility,financial savings,and security.However,information shoplifting poses significant threats,potentially leading to poor performance and privacy breaches.Blockchain-based cognitive computing can help protect and maintain information security and privacy in cloud platforms,ensuring businesses can focus on business development.To ensure data security in cloud platforms,this research proposed a blockchain-based Hybridized Data Driven Cognitive Computing(HD2C)model.However,the proposed HD2C framework addresses breaches of the privacy information of mixed participants of the Internet of Things(IoT)in the cloud.HD2C is developed by combining Federated Learning(FL)with a Blockchain consensus algorithm to connect smart contracts with Proof of Authority.The“Data Island”problem can be solved by FL’s emphasis on privacy and lightning-fast processing,while Blockchain provides a decentralized incentive structure that is impervious to poisoning.FL with Blockchain allows quick consensus through smart member selection and verification.The HD2C paradigm significantly improves the computational processing efficiency of intelligent manufacturing.Extensive analysis results derived from IIoT datasets confirm HD2C superiority.When compared to other consensus algorithms,the Blockchain PoA’s foundational cost is significant.The accuracy and memory utilization evaluation results predict the total benefits of the system.In comparison to the values 0.004 and 0.04,the value of 0.4 achieves good accuracy.According to the experiment results,the number of transactions per second has minimal impact on memory requirements.The findings of this study resulted in the development of a brand-new IIoT framework based on blockchain technology.
