Selenium nanoparticles(SeNPs)have been demonstrated potential for use in diseases associated with oxidative stress.Functionalized SeNPs with lower toxicity and higher biocompatibility could bring better therapeutic ac...Selenium nanoparticles(SeNPs)have been demonstrated potential for use in diseases associated with oxidative stress.Functionalized SeNPs with lower toxicity and higher biocompatibility could bring better therapeutic activity and clinical application value.Herein,this work was conducted to investigate the protective effect of Pleurotus tuber-regium polysaccharide-protein complex funtionnalized SeNPs(PTR-SeNPs)against acetaminophen(APAP)-induced oxidative injure in HepG2 cells and C57BL/6J mouse liver.Further elucidation of the underlying molecular mechanism,in particular their modulation of Nrf2 signaling pathway was also performed.The results showed that PTR-SeNPs could significantly ameliorate APAP-induced oxidative injury as evidenced by a range of biochemical analysis,histopathological examination and immunoblotting study.PTR-SeNPs could hosphorylate and activate PKCδ,depress Keap1,and increase nuclear accumulation of Nrf2,resulting in upregulation of GCLC,GCLM,HO-1 and NQO-1 expression.Besides,PTR-SeNPs suppressed the biotransformation of APAP to generate intracellular ROS through CYP 2E1 inhibition,restoring the mitochondrial morphology.Furthermore,the protective effect of PTR-SeNPs against APAP induced hepatotoxicity was weakened as Nrf2 was depleted in vivo,indicating the pivotal role of Nrf2 signaling pathway in PTR-SeNPs mediated hepatoprotective efficacy.Being a potential hepatic protectant,PTR-SeNPs could serve as a new source of selenium supplement for health-promoting and biomedical applications.展开更多
As 5th Generation(5G)and Beyond 5G(B5G)networks become increasingly prevalent,ensuring not only networksecurity but also the security and reliability of the applications,the so-called network applications,becomesof pa...As 5th Generation(5G)and Beyond 5G(B5G)networks become increasingly prevalent,ensuring not only networksecurity but also the security and reliability of the applications,the so-called network applications,becomesof paramount importance.This paper introduces a novel integrated model architecture,combining a networkapplication validation framework with an AI-driven reactive system to enhance security in real-time.The proposedmodel leverages machine learning(ML)and artificial intelligence(AI)to dynamically monitor and respond tosecurity threats,effectively mitigating potential risks before they impact the network infrastructure.This dualapproach not only validates the functionality and performance of network applications before their real deploymentbut also enhances the network’s ability to adapt and respond to threats as they arise.The implementation ofthis model,in the shape of an architecture deployed in two distinct sites,demonstrates its practical viability andeffectiveness.Integrating application validation with proactive threat detection and response,the proposed modeladdresses critical security challenges unique to 5G infrastructures.This paper details the model,architecture’sdesign,implementation,and evaluation of this solution,illustrating its potential to improve network securitymanagement in 5G environments significantly.Our findings highlight the architecture’s capability to ensure boththe operational integrity of network applications and the security of the underlying infrastructure,presenting asignificant advancement in network security.展开更多
Porcine reproductive and respiratory syndrome(PRRS)is a globally prevalent contagious disease caused by the positive-strand RNA PRRS virus(PRRSV),resulting in substantial economic losses in the swine industry.Modifyin...Porcine reproductive and respiratory syndrome(PRRS)is a globally prevalent contagious disease caused by the positive-strand RNA PRRS virus(PRRSV),resulting in substantial economic losses in the swine industry.Modifying the CD163 SRCR5 domain,either through deletion or substitution,can eff1ectively confer resistance to PRRSV infection in pigs.However,large fragment modifications in pigs inevitably raise concerns about potential adverse effects on growth performance.Reducing the impact of genetic modifications on normal physiological functions is a promising direction for developing PRRSV-resistant pigs.In the current study,we identified a specific functional amino acid in CD163 that influences PRRSV proliferation.Viral infection experiments conducted on Marc145 and PK-15CD163 cells illustrated that the mE535G or corresponding pE529G mutations markedly inhibited highly pathogenic PRRSV(HP-PRRSV)proliferation by preventing viral binding and entry.Furthermore,individual viral challenge tests revealed that pigs with the E529G mutation had viral loads two orders of magnitude lower than wild-type(WT)pigs,confirming effective resistance to HP-PRRSV.Examination of the physiological indicators and scavenger function of CD163 verified no significant differences between the WT and E529G pigs.These findings suggest that E529G pigs can be used for breeding PRRSV-resistant pigs,providing novel insights into controlling future PRRSV outbreaks.展开更多
Future 6G communications are envisioned to enable a large catalogue of pioneering applications.These will range from networked Cyber-Physical Systems to edge computing devices,establishing real-time feedback control l...Future 6G communications are envisioned to enable a large catalogue of pioneering applications.These will range from networked Cyber-Physical Systems to edge computing devices,establishing real-time feedback control loops critical for managing Industry 5.0 deployments,digital agriculture systems,and essential infrastructures.The provision of extensive machine-type communications through 6G will render many of these innovative systems autonomous and unsupervised.While full automation will enhance industrial efficiency significantly,it concurrently introduces new cyber risks and vulnerabilities.In particular,unattended systems are highly susceptible to trust issues:malicious nodes and false information can be easily introduced into control loops.Additionally,Denialof-Service attacks can be executed by inundating the network with valueless noise.Current anomaly detection schemes require the entire transformation of the control software to integrate new steps and can only mitigate anomalies that conform to predefined mathematical models.Solutions based on an exhaustive data collection to detect anomalies are precise but extremely slow.Standard models,with their limited understanding of mobile networks,can achieve precision rates no higher than 75%.Therefore,more general and transversal protection mechanisms are needed to detect malicious behaviors transparently.This paper introduces a probabilistic trust model and control algorithm designed to address this gap.The model determines the probability of any node to be trustworthy.Communication channels are pruned for those nodes whose probability is below a given threshold.The trust control algorithmcomprises three primary phases,which feed themodel with three different probabilities,which are weighted and combined.Initially,anomalous nodes are identified using Gaussian mixture models and clustering technologies.Next,traffic patterns are studied using digital Bessel functions and the functional scalar product.Finally,the information coherence and content are analyzed.The noise content and abnormal information sequences are detected using a Volterra filter and a bank of Finite Impulse Response filters.An experimental validation based on simulation tools and environments was carried out.Results show the proposed solution can successfully detect up to 92%of malicious data injection attacks.展开更多
Maize stalk rot reduces grain yield and quality.Information about the genetics of resistance to maize stalk rot could help breeders design effective breeding strategies for the trait.Genomic prediction may be a more e...Maize stalk rot reduces grain yield and quality.Information about the genetics of resistance to maize stalk rot could help breeders design effective breeding strategies for the trait.Genomic prediction may be a more effective breeding strategy for stalk-rot resistance than marker-assisted selection.We performed a genome-wide association study(GWAS)and genomic prediction of resistance in testcross hybrids of 677 inbred lines from the Tuxpe?o and non-Tuxpe?o heterotic pools grown in three environments and genotyped with 200,681 single-nucleotide polymorphisms(SNPs).Eighteen SNPs associated with stalk rot shared genomic regions with gene families previously associated with plant biotic and abiotic responses.More favorable SNP haplotypes traced to tropical than to temperate progenitors of the inbred lines.Incorporating genotype-by-environment(G×E)interaction increased genomic prediction accuracy.展开更多
The current resource allocation in 5G vehicular networks for mobile cloud communication faces several challenges,such as low user utilization,unbalanced resource allocation,and extended adaptive allocation time.We pro...The current resource allocation in 5G vehicular networks for mobile cloud communication faces several challenges,such as low user utilization,unbalanced resource allocation,and extended adaptive allocation time.We propose an adaptive allocation algorithm for mobile cloud communication resources in 5G vehicular networks to address these issues.This study analyzes the components of the 5G vehicular network architecture to determine the performance of different components.It is ascertained that the communication modes in 5G vehicular networks for mobile cloud communication include in-band and out-of-band modes.Furthermore,this study analyzes the single-hop and multi-hop modes in mobile cloud communication and calculates the resource transmission rate and bandwidth in different communication modes.The study also determines the scenario of one-way and two-way vehicle lane cloud communication network connectivity,calculates the probability of vehicle network connectivity under different mobile cloud communication radii,and determines the amount of cloud communication resources required by vehicles in different lane scenarios.Based on the communication status of users in 5G vehicular networks,this study calculates the bandwidth and transmission rate of the allocated channels using Shannon’s formula.It determines the adaptive allocation of cloud communication resources,introduces an objective function to obtain the optimal solution after allocation,and completes the adaptive allocation process.The experimental results demonstrate that,with the application of the proposed method,the maximum utilization of user communication resources reaches approximately 99%.The balance coefficient curve approaches 1,and the allocation time remains under 2 s.This indicates that the proposed method has higher adaptive allocation efficiency.展开更多
Background: Studies have shown a strong correlation between the growth of E2 in serum and estrone-3-glucuronide (E1-3G) in urine during ovarian stimulation. Thus, we developed theoretical models for using urinary E1-3...Background: Studies have shown a strong correlation between the growth of E2 in serum and estrone-3-glucuronide (E1-3G) in urine during ovarian stimulation. Thus, we developed theoretical models for using urinary E1-3G in ovarian stimulation and focused on their experimental verification and analysis. Methods: A prospective, observational pilot study was conducted involving 54 patients who underwent 54 cycles of ovarian stimulation. The goal was to establish the growth rate of urinary E1-3G during the course of stimulation and to determine the daily upper and lower limits of growth rates at which stimulation is appropriate and safe. Controlled ovarian stimulation was performed using two different stimulation protocols—an antagonist protocol in 25 cases and a progestin-primed ovarian stimulation protocol (PPOS) in 29 cases, with fixed doses of gonadotropins. From the second day of stimulation, patients self-measured their daily urine E1-3G levels at home using a portable analyzer. In parallel, a standard ultrasound follow-up protocol accompanied by a determination of E2, LH, and P levels was applied to optimally control stimulation. Results: The average daily growth rates in both groups were about 50%. The daily increase in E1-3G for the antagonist protocol ranged from 14% to 79%, while they were 28% to 79% for the PPOS protocol. Conclusion: This is the first study to analyze the dynamics of E1-3G in two different protocols and to estimate the limits of its increase during the entire course of the stimulation. The results confirm our theoretical model for the viability of using urinary E1-3G for monitoring ovarian stimulation.展开更多
基金financially supported by National Natural Science Foundation of China(81700524)Natural Science Foundation of Fujian Province(2022J01866)from Fujian Provincial Department of Science and Technology+1 种基金Key Project of Fujian University of Traditional Chinese Medicine(X2021019)Collaborative Innovation and Platform Establishment Project of Department of Science and Technology of Guangdong Province(2019A050520003)。
文摘Selenium nanoparticles(SeNPs)have been demonstrated potential for use in diseases associated with oxidative stress.Functionalized SeNPs with lower toxicity and higher biocompatibility could bring better therapeutic activity and clinical application value.Herein,this work was conducted to investigate the protective effect of Pleurotus tuber-regium polysaccharide-protein complex funtionnalized SeNPs(PTR-SeNPs)against acetaminophen(APAP)-induced oxidative injure in HepG2 cells and C57BL/6J mouse liver.Further elucidation of the underlying molecular mechanism,in particular their modulation of Nrf2 signaling pathway was also performed.The results showed that PTR-SeNPs could significantly ameliorate APAP-induced oxidative injury as evidenced by a range of biochemical analysis,histopathological examination and immunoblotting study.PTR-SeNPs could hosphorylate and activate PKCδ,depress Keap1,and increase nuclear accumulation of Nrf2,resulting in upregulation of GCLC,GCLM,HO-1 and NQO-1 expression.Besides,PTR-SeNPs suppressed the biotransformation of APAP to generate intracellular ROS through CYP 2E1 inhibition,restoring the mitochondrial morphology.Furthermore,the protective effect of PTR-SeNPs against APAP induced hepatotoxicity was weakened as Nrf2 was depleted in vivo,indicating the pivotal role of Nrf2 signaling pathway in PTR-SeNPs mediated hepatoprotective efficacy.Being a potential hepatic protectant,PTR-SeNPs could serve as a new source of selenium supplement for health-promoting and biomedical applications.
文摘As 5th Generation(5G)and Beyond 5G(B5G)networks become increasingly prevalent,ensuring not only networksecurity but also the security and reliability of the applications,the so-called network applications,becomesof paramount importance.This paper introduces a novel integrated model architecture,combining a networkapplication validation framework with an AI-driven reactive system to enhance security in real-time.The proposedmodel leverages machine learning(ML)and artificial intelligence(AI)to dynamically monitor and respond tosecurity threats,effectively mitigating potential risks before they impact the network infrastructure.This dualapproach not only validates the functionality and performance of network applications before their real deploymentbut also enhances the network’s ability to adapt and respond to threats as they arise.The implementation ofthis model,in the shape of an architecture deployed in two distinct sites,demonstrates its practical viability andeffectiveness.Integrating application validation with proactive threat detection and response,the proposed modeladdresses critical security challenges unique to 5G infrastructures.This paper details the model,architecture’sdesign,implementation,and evaluation of this solution,illustrating its potential to improve network securitymanagement in 5G environments significantly.Our findings highlight the architecture’s capability to ensure boththe operational integrity of network applications and the security of the underlying infrastructure,presenting asignificant advancement in network security.
基金Major Scientific and Technological Projects in Agricultural Biological Breeding of China(2023ZD0404302)Youth Program of National Natural Science Foundation of China(32202754)。
文摘Porcine reproductive and respiratory syndrome(PRRS)is a globally prevalent contagious disease caused by the positive-strand RNA PRRS virus(PRRSV),resulting in substantial economic losses in the swine industry.Modifying the CD163 SRCR5 domain,either through deletion or substitution,can eff1ectively confer resistance to PRRSV infection in pigs.However,large fragment modifications in pigs inevitably raise concerns about potential adverse effects on growth performance.Reducing the impact of genetic modifications on normal physiological functions is a promising direction for developing PRRSV-resistant pigs.In the current study,we identified a specific functional amino acid in CD163 that influences PRRSV proliferation.Viral infection experiments conducted on Marc145 and PK-15CD163 cells illustrated that the mE535G or corresponding pE529G mutations markedly inhibited highly pathogenic PRRSV(HP-PRRSV)proliferation by preventing viral binding and entry.Furthermore,individual viral challenge tests revealed that pigs with the E529G mutation had viral loads two orders of magnitude lower than wild-type(WT)pigs,confirming effective resistance to HP-PRRSV.Examination of the physiological indicators and scavenger function of CD163 verified no significant differences between the WT and E529G pigs.These findings suggest that E529G pigs can be used for breeding PRRSV-resistant pigs,providing novel insights into controlling future PRRSV outbreaks.
基金funding by Comunidad de Madrid within the framework of the Multiannual Agreement with Universidad Politécnica de Madrid to encourage research by young doctors(PRINCE project).
文摘Future 6G communications are envisioned to enable a large catalogue of pioneering applications.These will range from networked Cyber-Physical Systems to edge computing devices,establishing real-time feedback control loops critical for managing Industry 5.0 deployments,digital agriculture systems,and essential infrastructures.The provision of extensive machine-type communications through 6G will render many of these innovative systems autonomous and unsupervised.While full automation will enhance industrial efficiency significantly,it concurrently introduces new cyber risks and vulnerabilities.In particular,unattended systems are highly susceptible to trust issues:malicious nodes and false information can be easily introduced into control loops.Additionally,Denialof-Service attacks can be executed by inundating the network with valueless noise.Current anomaly detection schemes require the entire transformation of the control software to integrate new steps and can only mitigate anomalies that conform to predefined mathematical models.Solutions based on an exhaustive data collection to detect anomalies are precise but extremely slow.Standard models,with their limited understanding of mobile networks,can achieve precision rates no higher than 75%.Therefore,more general and transversal protection mechanisms are needed to detect malicious behaviors transparently.This paper introduces a probabilistic trust model and control algorithm designed to address this gap.The model determines the probability of any node to be trustworthy.Communication channels are pruned for those nodes whose probability is below a given threshold.The trust control algorithmcomprises three primary phases,which feed themodel with three different probabilities,which are weighted and combined.Initially,anomalous nodes are identified using Gaussian mixture models and clustering technologies.Next,traffic patterns are studied using digital Bessel functions and the functional scalar product.Finally,the information coherence and content are analyzed.The noise content and abnormal information sequences are detected using a Volterra filter and a bank of Finite Impulse Response filters.An experimental validation based on simulation tools and environments was carried out.Results show the proposed solution can successfully detect up to 92%of malicious data injection attacks.
基金funded by the CGIAR Research Program(CRP)on MAIZEthe USAID through the Accelerating Genetic Gains Supplemental Project(Amend.No.9 MTO 069033),and the One CGIAR Initiative on Accelerated Breeding+1 种基金funding from the governments of Australia,Belgium,Canada,China,France,India,Japan,the Republic of Korea,Mexico,the Netherlands,New Zealand,Norway,Sweden,Switzerland,the United Kingdom,the United States,and the World Banksupported by the China Scholarship Council。
文摘Maize stalk rot reduces grain yield and quality.Information about the genetics of resistance to maize stalk rot could help breeders design effective breeding strategies for the trait.Genomic prediction may be a more effective breeding strategy for stalk-rot resistance than marker-assisted selection.We performed a genome-wide association study(GWAS)and genomic prediction of resistance in testcross hybrids of 677 inbred lines from the Tuxpe?o and non-Tuxpe?o heterotic pools grown in three environments and genotyped with 200,681 single-nucleotide polymorphisms(SNPs).Eighteen SNPs associated with stalk rot shared genomic regions with gene families previously associated with plant biotic and abiotic responses.More favorable SNP haplotypes traced to tropical than to temperate progenitors of the inbred lines.Incorporating genotype-by-environment(G×E)interaction increased genomic prediction accuracy.
基金This research was supported by Science and Technology Research Project of Education Department of Jiangxi Province,China(Nos.GJJ2206701,GJJ2206717).
文摘The current resource allocation in 5G vehicular networks for mobile cloud communication faces several challenges,such as low user utilization,unbalanced resource allocation,and extended adaptive allocation time.We propose an adaptive allocation algorithm for mobile cloud communication resources in 5G vehicular networks to address these issues.This study analyzes the components of the 5G vehicular network architecture to determine the performance of different components.It is ascertained that the communication modes in 5G vehicular networks for mobile cloud communication include in-band and out-of-band modes.Furthermore,this study analyzes the single-hop and multi-hop modes in mobile cloud communication and calculates the resource transmission rate and bandwidth in different communication modes.The study also determines the scenario of one-way and two-way vehicle lane cloud communication network connectivity,calculates the probability of vehicle network connectivity under different mobile cloud communication radii,and determines the amount of cloud communication resources required by vehicles in different lane scenarios.Based on the communication status of users in 5G vehicular networks,this study calculates the bandwidth and transmission rate of the allocated channels using Shannon’s formula.It determines the adaptive allocation of cloud communication resources,introduces an objective function to obtain the optimal solution after allocation,and completes the adaptive allocation process.The experimental results demonstrate that,with the application of the proposed method,the maximum utilization of user communication resources reaches approximately 99%.The balance coefficient curve approaches 1,and the allocation time remains under 2 s.This indicates that the proposed method has higher adaptive allocation efficiency.
文摘Background: Studies have shown a strong correlation between the growth of E2 in serum and estrone-3-glucuronide (E1-3G) in urine during ovarian stimulation. Thus, we developed theoretical models for using urinary E1-3G in ovarian stimulation and focused on their experimental verification and analysis. Methods: A prospective, observational pilot study was conducted involving 54 patients who underwent 54 cycles of ovarian stimulation. The goal was to establish the growth rate of urinary E1-3G during the course of stimulation and to determine the daily upper and lower limits of growth rates at which stimulation is appropriate and safe. Controlled ovarian stimulation was performed using two different stimulation protocols—an antagonist protocol in 25 cases and a progestin-primed ovarian stimulation protocol (PPOS) in 29 cases, with fixed doses of gonadotropins. From the second day of stimulation, patients self-measured their daily urine E1-3G levels at home using a portable analyzer. In parallel, a standard ultrasound follow-up protocol accompanied by a determination of E2, LH, and P levels was applied to optimally control stimulation. Results: The average daily growth rates in both groups were about 50%. The daily increase in E1-3G for the antagonist protocol ranged from 14% to 79%, while they were 28% to 79% for the PPOS protocol. Conclusion: This is the first study to analyze the dynamics of E1-3G in two different protocols and to estimate the limits of its increase during the entire course of the stimulation. The results confirm our theoretical model for the viability of using urinary E1-3G for monitoring ovarian stimulation.
