The receptor for activated C kinase 1(RACK1)is a protein that plays a crucial role in various signaling pathways and is involved in the pathogenesis of Alzheimer's disease(AD),a prevalent neurodegenerative disease...The receptor for activated C kinase 1(RACK1)is a protein that plays a crucial role in various signaling pathways and is involved in the pathogenesis of Alzheimer's disease(AD),a prevalent neurodegenerative disease.RACK1 is highly expressed in neuronal cells of the central nervous system and regulates the pathogenesis of AD.Specifically,RACK1 is involved in regulation of the amyloid-β precursor protein processing through α-or β-secretase by binding to different protein kinase C isoforms.Additionally,RACK1 promotes synaptogenesis and synaptic plasticity by inhibiting N-methyl-D-aspartate receptors and activating gamma-aminobutyric acid A receptors,thereby preventing neuronal excitotoxicity.RACK1 also assembles inflammasomes that are involved in various neuroinflammatory pathways,such as nuclear factor-kappa B,tumor necrosis factor-alpha,and NOD-like receptor family pyrin domain-containing 3 pathways.The potential to design therapeutics that block amyloid-β accumulation and inflammation or precisely regulate synaptic plasticity represents an attractive therapeutic strategy,in which RACK1 is a potential target.In this review,we summarize the contribution of RACK1 to the pathogenesis of AD and its potential as a therapeutic target.展开更多
Turbulent flow through a trash rack of bars of rectangular and biconvex shapes is considered. A trash rack is composed of an array of bars fitted into a hydro-electric power station to prevent debris and fish to enter...Turbulent flow through a trash rack of bars of rectangular and biconvex shapes is considered. A trash rack is composed of an array of bars fitted into a hydro-electric power station to prevent debris and fish to enter the waterway towards the turbine. The work is directed towards modeling a large number of bars for which the flow turn out to have a periodic structure. It is here shown that this case can be simplified with the flow past a single bar together with periodic boundary conditions. Using this approach the head loss is derived for different angles of attack α and blockages P for two shapes of the rack, a rectangular bar and an aerodynamically shaped biconvex bar. It is found that overall loss of the biconvex bars is in general about 15% of the loss for the rectangular case for small angles of attack. For large angle of attack this difference diminishes. Of interest for the biconvex bars is also a local minimum in the head loss for angles approximately greater than 20°and for a blockage P around 0.35. This combination of parameters gives a low loss together with an efficient barrier for debris and fishes.展开更多
Environmental pollution has had substantial impacts on human life,and trash is one of the main sources of such pollution in most countries.Trash classi-fication from a collection of trash images can limit the overloadi...Environmental pollution has had substantial impacts on human life,and trash is one of the main sources of such pollution in most countries.Trash classi-fication from a collection of trash images can limit the overloading of garbage dis-posal systems and efficiently promote recycling activities;thus,development of such a classification system is topical and urgent.This paper proposed an effective trash classification system that relies on a classification module embedded in a hard-ware setup to classify trash in real time.An image dataset isfirst augmented to enhance the images before classifying them as either inorganic or organic trash.The deep learning–based ResNet-50 model,an improved version of the ResNet model,is used to classify trash from the dataset of trash images.The experimental results,which are tested both on the dataset and in real time,show that ResNet-50 had an average accuracy of 96%,higher than that of related models.Moreover,integrating the classification module into a Raspberry Pi computer,which con-trolled the trash bin slide so that garbage fell into the appropriate bin for inorganic or organic waste,created a complete trash classification system.This proves the efficiency and high applicability of the proposed system.展开更多
基金supported by grants from the National Natural Science Foundation of China(Grant No.82071395)the Natural Science Foundation of Chongqing(Grant Nos.cstc2021ycjh-bgzxm0186,cstc2020jcyj-zdxmX0004,and cstc2021jcyj-bsh0023)the CQMU Program for Youth Innovation in Future Medicine(Grant No.W0044).
文摘The receptor for activated C kinase 1(RACK1)is a protein that plays a crucial role in various signaling pathways and is involved in the pathogenesis of Alzheimer's disease(AD),a prevalent neurodegenerative disease.RACK1 is highly expressed in neuronal cells of the central nervous system and regulates the pathogenesis of AD.Specifically,RACK1 is involved in regulation of the amyloid-β precursor protein processing through α-or β-secretase by binding to different protein kinase C isoforms.Additionally,RACK1 promotes synaptogenesis and synaptic plasticity by inhibiting N-methyl-D-aspartate receptors and activating gamma-aminobutyric acid A receptors,thereby preventing neuronal excitotoxicity.RACK1 also assembles inflammasomes that are involved in various neuroinflammatory pathways,such as nuclear factor-kappa B,tumor necrosis factor-alpha,and NOD-like receptor family pyrin domain-containing 3 pathways.The potential to design therapeutics that block amyloid-β accumulation and inflammation or precisely regulate synaptic plasticity represents an attractive therapeutic strategy,in which RACK1 is a potential target.In this review,we summarize the contribution of RACK1 to the pathogenesis of AD and its potential as a therapeutic target.
基金The Swedish Agency of Energy and Stand Up for Energy
文摘Turbulent flow through a trash rack of bars of rectangular and biconvex shapes is considered. A trash rack is composed of an array of bars fitted into a hydro-electric power station to prevent debris and fish to enter the waterway towards the turbine. The work is directed towards modeling a large number of bars for which the flow turn out to have a periodic structure. It is here shown that this case can be simplified with the flow past a single bar together with periodic boundary conditions. Using this approach the head loss is derived for different angles of attack α and blockages P for two shapes of the rack, a rectangular bar and an aerodynamically shaped biconvex bar. It is found that overall loss of the biconvex bars is in general about 15% of the loss for the rectangular case for small angles of attack. For large angle of attack this difference diminishes. Of interest for the biconvex bars is also a local minimum in the head loss for angles approximately greater than 20°and for a blockage P around 0.35. This combination of parameters gives a low loss together with an efficient barrier for debris and fishes.
文摘Environmental pollution has had substantial impacts on human life,and trash is one of the main sources of such pollution in most countries.Trash classi-fication from a collection of trash images can limit the overloading of garbage dis-posal systems and efficiently promote recycling activities;thus,development of such a classification system is topical and urgent.This paper proposed an effective trash classification system that relies on a classification module embedded in a hard-ware setup to classify trash in real time.An image dataset isfirst augmented to enhance the images before classifying them as either inorganic or organic trash.The deep learning–based ResNet-50 model,an improved version of the ResNet model,is used to classify trash from the dataset of trash images.The experimental results,which are tested both on the dataset and in real time,show that ResNet-50 had an average accuracy of 96%,higher than that of related models.Moreover,integrating the classification module into a Raspberry Pi computer,which con-trolled the trash bin slide so that garbage fell into the appropriate bin for inorganic or organic waste,created a complete trash classification system.This proves the efficiency and high applicability of the proposed system.
