It has been shown clinically that continuous removal of ischemia/reperfusion-induced reactive oxygen species is not conducive to the recovery of late stroke.Indeed,previous studies have shown that excessive increases ...It has been shown clinically that continuous removal of ischemia/reperfusion-induced reactive oxygen species is not conducive to the recovery of late stroke.Indeed,previous studies have shown that excessive increases in hypochlorous acid after stroke can cause severe damage to brain tissue.Our previous studies have found that a small amount of hypochlorous acid still exists in the later stage of stroke,but its specific role and mechanism are currently unclear.To simulate stroke in vivo,a middle cerebral artery occlusion rat model was established,with an oxygen-glucose deprivation/reoxygenation model established in vitro to mimic stroke.We found that in the early stage(within 24 hours)of ischemic stroke,neutrophils produced a large amount of hypochlorous acid,while in the recovery phase(10 days after stroke),microglia were activated and produced a small amount of hypochlorous acid.Further,in acute stroke in rats,hypochlorous acid production was prevented using a hypochlorous acid scavenger,taurine,or myeloperoxidase inhibitor,4-aminobenzoic acid hydrazide.Our results showed that high levels of hypochlorous acid(200μM)induced neuronal apoptosis after oxygen/glucose deprivation/reoxygenation.However,in the recovery phase of the middle cerebral artery occlusion model,a moderate level of hypochlorous acid promoted the proliferation and differentiation of neural stem cells into neurons and astrocytes.This suggests that hypochlorous acid plays different roles at different phases of cerebral ischemia/reperfusion injury.Lower levels of hypochlorous acid(5 and 100μM)promoted nuclear translocation ofβ-catenin.By transfection of single-site mutation plasmids,we found that hypochlorous acid induced chlorination of theβ-catenin tyrosine 30 residue,which promoted nuclear translocation.Altogether,our study indicates that maintaining low levels of hypochlorous acid plays a key role in the recovery of neurological function.展开更多
Over 1.3 million people die annually in traffic accidents,and this tragic fact highlights the urgent need to enhance the intelligence of traffic safety and control systems.In modern industrial and technological applic...Over 1.3 million people die annually in traffic accidents,and this tragic fact highlights the urgent need to enhance the intelligence of traffic safety and control systems.In modern industrial and technological applications and collaborative edge intelligence,control systems are crucial for ensuring efficiency and safety.However,deficiencies in these systems can lead to significant operational risks.This paper uses edge intelligence to address the challenges of achieving target speeds and improving efficiency in vehicle control,particularly the limitations of traditional Proportional-Integral-Derivative(PID)controllers inmanaging nonlinear and time-varying dynamics,such as varying road conditions and vehicle behavior,which often result in substantial discrepancies between desired and actual speeds,as well as inefficiencies due to manual parameter adjustments.The paper uses edge intelligence to propose a novel PID control algorithm that integrates Backpropagation(BP)neural networks to enhance robustness and adaptability.The BP neural network is first trained to capture the nonlinear dynamic characteristics of the vehicle.Thetrained network is then combined with the PID controller to forma hybrid control strategy.The output layer of the neural network directly adjusts the PIDparameters(k_(p),k_(i),k_(d)),optimizing performance for specific driving scenarios through self-learning and weight adjustments.Simulation experiments demonstrate that our BP neural network-based PID design significantly outperforms traditional methods,with the response time for acceleration from 0 to 1 m/s improved from 0.25 s to just 0.065 s.Furthermore,real-world tests on an intelligent vehicle show its ability to make timely adjustments in response to complex road conditions,ensuring consistent speed maintenance and enhancing overall system performance.展开更多
Skin is the largest organ of the human body and a possible source of stem cells for research and cell-based therapy. We have isolated a population of mesenchymal stem cell-like pluripotent cells from human epidermis, ...Skin is the largest organ of the human body and a possible source of stem cells for research and cell-based therapy. We have isolated a population of mesenchymal stem cell-like pluripotent cells from human epidermis, termed human (h) EMSCPCs. This preliminary study tested if these hEMSCPCs can be induced to differentiate into neural-like cells. Human EMSCPCs were first cultured for four to seven days in a serum-free neural stem cell (NSC) medium for pre-induction. During pre-induction, hEMSCPCs coalesced into dense spheres that resembled neural rosettes. In the presence of a conditioned differentiation medium, pre-induced cells took on the morphological characteristics of neural cells, including slender projections with inflated or claw-like ends that contacted the soma or projections of other cells as revealed by confocal microscopy. Moreover, these differentiating cells expressed the neural-specific markers β-III tubulin, MAP2, GFAP, and synapsin I as evidenced by immunocytochemistry. Both pre-induced hEMSCPCs and uninduced hEMSCPCs were labeled with CM-DiI and transplanted into the vitreous cavities of nude mice. Transplanted cells were examined four weeks later in frozen eyeball sections by immunofluorescence staining, which demonstrated superior retinal migration and neural differentiation of pre-induced cells. Our study is the first to demonstrate that hEMSCPCs possess the capacity to differentiate into neural-like cells, suggesting potential uses for the treatment of retinal diseases such as age-related macular degeneration.展开更多
The integration of technologies like artificial intelligence,6G,and vehicular ad-hoc networks holds great potential to meet the communication demands of the Internet of Vehicles and drive the advancement of vehicle ap...The integration of technologies like artificial intelligence,6G,and vehicular ad-hoc networks holds great potential to meet the communication demands of the Internet of Vehicles and drive the advancement of vehicle applications.However,these advancements also generate a surge in data processing requirements,necessitating the offloading of vehicular tasks to edge servers due to the limited computational capacity of vehicles.Despite recent advancements,the robustness and scalability of the existing approaches with respect to the number of vehicles and edge servers and their resources,as well as privacy,remain a concern.In this paper,a lightweight offloading strategy that leverages ubiquitous connectivity through the Space Air Ground Integrated Vehicular Network architecture while ensuring privacy preservation is proposed.The Internet of Vehicles(IoV)environment is first modeled as a graph,with vehicles and base stations as nodes,and their communication links as edges.Secondly,vehicular applications are offloaded to suitable servers based on latency using an attention-based heterogeneous graph neural network(HetGNN)algorithm.Subsequently,a differential privacy stochastic gradient descent trainingmechanism is employed for privacypreserving of vehicles and offloading inference.Finally,the simulation results demonstrated that the proposedHetGNN method shows good performance with 0.321 s of inference time,which is 42.68%,63.93%,30.22%,and 76.04% less than baseline methods such as Deep Deterministic Policy Gradient,Deep Q Learning,Deep Neural Network,and Genetic Algorithm,respectively.展开更多
The recent progress in neural stem cells （NSCs） research has shed lights on possibility of repair and restoration of neuronal function in neurodegenerative diseases using stem cells. Induction of stem cells differen...The recent progress in neural stem cells （NSCs） research has shed lights on possibility of repair and restoration of neuronal function in neurodegenerative diseases using stem cells. Induction of stem cells differentiate into mature neurons is critical to achieve the clinical applications of NSCs. At present, molecular mechanisms modulating NSC differentiation are not fully understood. Differentiation of stem cells into neuronal and glial cells involves an array of changes in expression of transcription factors. Transcription factors then trigger the expression of a variety of central nervous system （CNS） genes that lead NSCs to differentiate towards different cell types. In this paper, we summarized the recent findings on the gene regulation of NSCs differentiation into neuronal cells.展开更多
基金supported by the Natural Science Foundation of Jiangsu Province of China,No.BK20211348(to SHQ)Xuzhou Basic Research Program,No.KC21030(to LYH)+1 种基金Leadership Program of Xuzhou Medical University,No.JBGS202203(to SHQ)Research Grant Council GRF of Hong Kong Special Administrative Region of China,No.17105220(to JGS)。
文摘It has been shown clinically that continuous removal of ischemia/reperfusion-induced reactive oxygen species is not conducive to the recovery of late stroke.Indeed,previous studies have shown that excessive increases in hypochlorous acid after stroke can cause severe damage to brain tissue.Our previous studies have found that a small amount of hypochlorous acid still exists in the later stage of stroke,but its specific role and mechanism are currently unclear.To simulate stroke in vivo,a middle cerebral artery occlusion rat model was established,with an oxygen-glucose deprivation/reoxygenation model established in vitro to mimic stroke.We found that in the early stage(within 24 hours)of ischemic stroke,neutrophils produced a large amount of hypochlorous acid,while in the recovery phase(10 days after stroke),microglia were activated and produced a small amount of hypochlorous acid.Further,in acute stroke in rats,hypochlorous acid production was prevented using a hypochlorous acid scavenger,taurine,or myeloperoxidase inhibitor,4-aminobenzoic acid hydrazide.Our results showed that high levels of hypochlorous acid(200μM)induced neuronal apoptosis after oxygen/glucose deprivation/reoxygenation.However,in the recovery phase of the middle cerebral artery occlusion model,a moderate level of hypochlorous acid promoted the proliferation and differentiation of neural stem cells into neurons and astrocytes.This suggests that hypochlorous acid plays different roles at different phases of cerebral ischemia/reperfusion injury.Lower levels of hypochlorous acid(5 and 100μM)promoted nuclear translocation ofβ-catenin.By transfection of single-site mutation plasmids,we found that hypochlorous acid induced chlorination of theβ-catenin tyrosine 30 residue,which promoted nuclear translocation.Altogether,our study indicates that maintaining low levels of hypochlorous acid plays a key role in the recovery of neurological function.
基金supported by the National Key Research and Development Program of China(No.2023YFF0715103)-financial supportNational Natural Science Foundation of China(Grant Nos.62306237 and 62006191)-financial support+1 种基金Key Research and Development Program of Shaanxi(Nos.2024GX-YBXM-149 and 2021ZDLGY15-04)-financial support,NorthwestUniversity Graduate Innovation Project(No.CX2023194)-financial supportNatural Science Foundation of Shaanxi(No.2023-JC-QN-0750)-financial support.
文摘Over 1.3 million people die annually in traffic accidents,and this tragic fact highlights the urgent need to enhance the intelligence of traffic safety and control systems.In modern industrial and technological applications and collaborative edge intelligence,control systems are crucial for ensuring efficiency and safety.However,deficiencies in these systems can lead to significant operational risks.This paper uses edge intelligence to address the challenges of achieving target speeds and improving efficiency in vehicle control,particularly the limitations of traditional Proportional-Integral-Derivative(PID)controllers inmanaging nonlinear and time-varying dynamics,such as varying road conditions and vehicle behavior,which often result in substantial discrepancies between desired and actual speeds,as well as inefficiencies due to manual parameter adjustments.The paper uses edge intelligence to propose a novel PID control algorithm that integrates Backpropagation(BP)neural networks to enhance robustness and adaptability.The BP neural network is first trained to capture the nonlinear dynamic characteristics of the vehicle.Thetrained network is then combined with the PID controller to forma hybrid control strategy.The output layer of the neural network directly adjusts the PIDparameters(k_(p),k_(i),k_(d)),optimizing performance for specific driving scenarios through self-learning and weight adjustments.Simulation experiments demonstrate that our BP neural network-based PID design significantly outperforms traditional methods,with the response time for acceleration from 0 to 1 m/s improved from 0.25 s to just 0.065 s.Furthermore,real-world tests on an intelligent vehicle show its ability to make timely adjustments in response to complex road conditions,ensuring consistent speed maintenance and enhancing overall system performance.
文摘Skin is the largest organ of the human body and a possible source of stem cells for research and cell-based therapy. We have isolated a population of mesenchymal stem cell-like pluripotent cells from human epidermis, termed human (h) EMSCPCs. This preliminary study tested if these hEMSCPCs can be induced to differentiate into neural-like cells. Human EMSCPCs were first cultured for four to seven days in a serum-free neural stem cell (NSC) medium for pre-induction. During pre-induction, hEMSCPCs coalesced into dense spheres that resembled neural rosettes. In the presence of a conditioned differentiation medium, pre-induced cells took on the morphological characteristics of neural cells, including slender projections with inflated or claw-like ends that contacted the soma or projections of other cells as revealed by confocal microscopy. Moreover, these differentiating cells expressed the neural-specific markers β-III tubulin, MAP2, GFAP, and synapsin I as evidenced by immunocytochemistry. Both pre-induced hEMSCPCs and uninduced hEMSCPCs were labeled with CM-DiI and transplanted into the vitreous cavities of nude mice. Transplanted cells were examined four weeks later in frozen eyeball sections by immunofluorescence staining, which demonstrated superior retinal migration and neural differentiation of pre-induced cells. Our study is the first to demonstrate that hEMSCPCs possess the capacity to differentiate into neural-like cells, suggesting potential uses for the treatment of retinal diseases such as age-related macular degeneration.
文摘The integration of technologies like artificial intelligence,6G,and vehicular ad-hoc networks holds great potential to meet the communication demands of the Internet of Vehicles and drive the advancement of vehicle applications.However,these advancements also generate a surge in data processing requirements,necessitating the offloading of vehicular tasks to edge servers due to the limited computational capacity of vehicles.Despite recent advancements,the robustness and scalability of the existing approaches with respect to the number of vehicles and edge servers and their resources,as well as privacy,remain a concern.In this paper,a lightweight offloading strategy that leverages ubiquitous connectivity through the Space Air Ground Integrated Vehicular Network architecture while ensuring privacy preservation is proposed.The Internet of Vehicles(IoV)environment is first modeled as a graph,with vehicles and base stations as nodes,and their communication links as edges.Secondly,vehicular applications are offloaded to suitable servers based on latency using an attention-based heterogeneous graph neural network(HetGNN)algorithm.Subsequently,a differential privacy stochastic gradient descent trainingmechanism is employed for privacypreserving of vehicles and offloading inference.Finally,the simulation results demonstrated that the proposedHetGNN method shows good performance with 0.321 s of inference time,which is 42.68%,63.93%,30.22%,and 76.04% less than baseline methods such as Deep Deterministic Policy Gradient,Deep Q Learning,Deep Neural Network,and Genetic Algorithm,respectively.
基金supported by the National Natural Science Foundation of China(No.30470587)the Natural Science Foundation of Jiangsu Province(No.BK2004037)the Department of Personnel of Jiangsu Province(No.L2134501).
文摘The recent progress in neural stem cells （NSCs） research has shed lights on possibility of repair and restoration of neuronal function in neurodegenerative diseases using stem cells. Induction of stem cells differentiate into mature neurons is critical to achieve the clinical applications of NSCs. At present, molecular mechanisms modulating NSC differentiation are not fully understood. Differentiation of stem cells into neuronal and glial cells involves an array of changes in expression of transcription factors. Transcription factors then trigger the expression of a variety of central nervous system （CNS） genes that lead NSCs to differentiate towards different cell types. In this paper, we summarized the recent findings on the gene regulation of NSCs differentiation into neuronal cells.
