Downregulation of the inwardly rectifying potassium channel Kir4.1 is a key step for inducing retinal Müller cell activation and interaction with other glial cells,which is involved in retinal ganglion cell apopt...Downregulation of the inwardly rectifying potassium channel Kir4.1 is a key step for inducing retinal Müller cell activation and interaction with other glial cells,which is involved in retinal ganglion cell apoptosis in glaucoma.Modulation of Kir4.1 expression in Müller cells may therefore be a potential strategy for attenuating retinal ganglion cell damage in glaucoma.In this study,we identified seven predicted phosphorylation sites in Kir4.1 and constructed lentiviral expression systems expressing Kir4.1 mutated at each site to prevent phosphorylation.Following this,we treated Müller glial cells in vitro and in vivo with the m Glu R I agonist DHPG to induce Kir4.1 or Kir4.1 Tyr^(9)Asp overexpression.We found that both Kir4.1 and Kir4.1 Tyr^(9)Asp overexpression inhibited activation of Müller glial cells.Subsequently,we established a rat model of chronic ocular hypertension by injecting microbeads into the anterior chamber and overexpressed Kir4.1 or Kir4.1 Tyr^(9)Asp in the eye,and observed similar results in Müller cells in vivo as those seen in vitro.Both Kir4.1 and Kir4.1 Tyr^(9)Asp overexpression inhibited Müller cell activation,regulated the balance of Bax/Bcl-2,and reduced the m RNA and protein levels of pro-inflammatory factors,including interleukin-1βand tumor necrosis factor-α.Furthermore,we investigated the regulatory effects of Kir4.1 and Kir4.1 Tyr^(9)Asp overexpression on the release of pro-inflammatory factors in a co-culture system of Müller glial cells and microglia.In this co-culture system,we observed elevated adenosine triphosphate concentrations in activated Müller cells,increased levels of translocator protein(a marker of microglial activation),and elevated interleukin-1βm RNA and protein levels in microglia induced by activated Müller cells.These changes could be reversed by Kir4.1 and Kir4.1 Tyr^(9)Asp overexpression in Müller cells.Kir4.1 overexpression,but not Kir4.1 Tyr^(9)Asp overexpression,reduced the number of proliferative and migratory microglia induced by activated Müller cells.Collectively,these results suggest that the tyrosine residue at position nine in Kir4.1 may serve as a functional modulation site in the retina in an experimental model of glaucoma.Kir4.1 and Kir4.1 Tyr^(9)Asp overexpression attenuated Müller cell activation,reduced ATP/P2X receptor–mediated interactions between glial cells,inhibited microglial activation,and decreased the synthesis and release of pro-inflammatory factors,consequently ameliorating retinal ganglion cell apoptosis in glaucoma.展开更多
Modern manufacturing processes have become more reliant on automation because of the accelerated transition from Industry 3.0 to Industry 4.0.Manual inspection of products on assembly lines remains inefficient,prone t...Modern manufacturing processes have become more reliant on automation because of the accelerated transition from Industry 3.0 to Industry 4.0.Manual inspection of products on assembly lines remains inefficient,prone to errors and lacks consistency,emphasizing the need for a reliable and automated inspection system.Leveraging both object detection and image segmentation approaches,this research proposes a vision-based solution for the detection of various kinds of tools in the toolkit using deep learning(DL)models.Two Intel RealSense D455f depth cameras were arranged in a top down configuration to capture both RGB and depth images of the toolkits.After applying multiple constraints and enhancing them through preprocessing and augmentation,a dataset consisting of 3300 annotated RGB-D photos was generated.Several DL models were selected through a comprehensive assessment of mean Average Precision(mAP),precision-recall equilibrium,inference latency(target≥30 FPS),and computational burden,resulting in a preference for YOLO and Region-based Convolutional Neural Networks(R-CNN)variants over ViT-based models due to the latter’s increased latency and resource requirements.YOLOV5,YOLOV8,YOLOV11,Faster R-CNN,and Mask R-CNN were trained on the annotated dataset and evaluated using key performance metrics(Recall,Accuracy,F1-score,and Precision).YOLOV11 demonstrated balanced excellence with 93.0%precision,89.9%recall,and a 90.6%F1-score in object detection,as well as 96.9%precision,95.3%recall,and a 96.5%F1-score in instance segmentation with an average inference time of 25 ms per frame(≈40 FPS),demonstrating real-time performance.Leveraging these results,a YOLOV11-based windows application was successfully deployed in a real-time assembly line environment,where it accurately processed live video streams to detect and segment tools within toolkits,demonstrating its practical effectiveness in industrial automation.The application is capable of precisely measuring socket dimensions by utilising edge detection techniques on YOLOv11 segmentation masks,in addition to detection and segmentation.This makes it possible to do specification-level quality control right on the assembly line,which improves the ability to examine things in real time.The implementation is a big step forward for intelligent manufacturing in the Industry 4.0 paradigm.It provides a scalable,efficient,and accurate way to do automated inspection and dimensional verification activities.展开更多
基金supported by the National Natural Science Foundation of China,Nos.32271043(to ZW)and 82171047(to YM)the both Science and Technology Major Project of Shanghai,No.2018SHZDZX01 and ZJLabShanghai Center for Brain Science and Brain-Inspired Technology(to ZW)。
文摘Downregulation of the inwardly rectifying potassium channel Kir4.1 is a key step for inducing retinal Müller cell activation and interaction with other glial cells,which is involved in retinal ganglion cell apoptosis in glaucoma.Modulation of Kir4.1 expression in Müller cells may therefore be a potential strategy for attenuating retinal ganglion cell damage in glaucoma.In this study,we identified seven predicted phosphorylation sites in Kir4.1 and constructed lentiviral expression systems expressing Kir4.1 mutated at each site to prevent phosphorylation.Following this,we treated Müller glial cells in vitro and in vivo with the m Glu R I agonist DHPG to induce Kir4.1 or Kir4.1 Tyr^(9)Asp overexpression.We found that both Kir4.1 and Kir4.1 Tyr^(9)Asp overexpression inhibited activation of Müller glial cells.Subsequently,we established a rat model of chronic ocular hypertension by injecting microbeads into the anterior chamber and overexpressed Kir4.1 or Kir4.1 Tyr^(9)Asp in the eye,and observed similar results in Müller cells in vivo as those seen in vitro.Both Kir4.1 and Kir4.1 Tyr^(9)Asp overexpression inhibited Müller cell activation,regulated the balance of Bax/Bcl-2,and reduced the m RNA and protein levels of pro-inflammatory factors,including interleukin-1βand tumor necrosis factor-α.Furthermore,we investigated the regulatory effects of Kir4.1 and Kir4.1 Tyr^(9)Asp overexpression on the release of pro-inflammatory factors in a co-culture system of Müller glial cells and microglia.In this co-culture system,we observed elevated adenosine triphosphate concentrations in activated Müller cells,increased levels of translocator protein(a marker of microglial activation),and elevated interleukin-1βm RNA and protein levels in microglia induced by activated Müller cells.These changes could be reversed by Kir4.1 and Kir4.1 Tyr^(9)Asp overexpression in Müller cells.Kir4.1 overexpression,but not Kir4.1 Tyr^(9)Asp overexpression,reduced the number of proliferative and migratory microglia induced by activated Müller cells.Collectively,these results suggest that the tyrosine residue at position nine in Kir4.1 may serve as a functional modulation site in the retina in an experimental model of glaucoma.Kir4.1 and Kir4.1 Tyr^(9)Asp overexpression attenuated Müller cell activation,reduced ATP/P2X receptor–mediated interactions between glial cells,inhibited microglial activation,and decreased the synthesis and release of pro-inflammatory factors,consequently ameliorating retinal ganglion cell apoptosis in glaucoma.
基金National Science and Technology Council,the Republic of China,under grants NSTC 113-2221-E-194-011-MY3 and Research Center on Artificial Intelligence and Sustainability,National Chung Cheng University under the research project grant titled“Generative Digital Twin System Design for Sustainable Smart City Development in Taiwan.
文摘Modern manufacturing processes have become more reliant on automation because of the accelerated transition from Industry 3.0 to Industry 4.0.Manual inspection of products on assembly lines remains inefficient,prone to errors and lacks consistency,emphasizing the need for a reliable and automated inspection system.Leveraging both object detection and image segmentation approaches,this research proposes a vision-based solution for the detection of various kinds of tools in the toolkit using deep learning(DL)models.Two Intel RealSense D455f depth cameras were arranged in a top down configuration to capture both RGB and depth images of the toolkits.After applying multiple constraints and enhancing them through preprocessing and augmentation,a dataset consisting of 3300 annotated RGB-D photos was generated.Several DL models were selected through a comprehensive assessment of mean Average Precision(mAP),precision-recall equilibrium,inference latency(target≥30 FPS),and computational burden,resulting in a preference for YOLO and Region-based Convolutional Neural Networks(R-CNN)variants over ViT-based models due to the latter’s increased latency and resource requirements.YOLOV5,YOLOV8,YOLOV11,Faster R-CNN,and Mask R-CNN were trained on the annotated dataset and evaluated using key performance metrics(Recall,Accuracy,F1-score,and Precision).YOLOV11 demonstrated balanced excellence with 93.0%precision,89.9%recall,and a 90.6%F1-score in object detection,as well as 96.9%precision,95.3%recall,and a 96.5%F1-score in instance segmentation with an average inference time of 25 ms per frame(≈40 FPS),demonstrating real-time performance.Leveraging these results,a YOLOV11-based windows application was successfully deployed in a real-time assembly line environment,where it accurately processed live video streams to detect and segment tools within toolkits,demonstrating its practical effectiveness in industrial automation.The application is capable of precisely measuring socket dimensions by utilising edge detection techniques on YOLOv11 segmentation masks,in addition to detection and segmentation.This makes it possible to do specification-level quality control right on the assembly line,which improves the ability to examine things in real time.The implementation is a big step forward for intelligent manufacturing in the Industry 4.0 paradigm.It provides a scalable,efficient,and accurate way to do automated inspection and dimensional verification activities.
