Objective:To investigate the mechanistic basis for the attenuation of bone degeneration by edible bird's nest(EBN)in ovariectomized rats.Methods:Forty-two female Sprage-Dawley rats were randomized into 7 groups(6 ...Objective:To investigate the mechanistic basis for the attenuation of bone degeneration by edible bird's nest(EBN)in ovariectomized rats.Methods:Forty-two female Sprage-Dawley rats were randomized into 7 groups(6 in each group).The ovariectomized(OVX)and OVX+6%,3%,and 1.5%EBN and OVX+estrogen groups were given standard rat chow alone,standard rat chow+6%,3%,and 1.5%EBN,or standard rat chow+estrogen therapy(0.2mg/kg per day),respectively.The sham-operation group was surgically opened without removing the ovaries.The control group did not have any surgical intervention.After 12 weeks of intervention,blood samples were taken for serum estrogen,osteocalcin,and osteoprotegerin,as well as the measurement of magnesium,calcium abd zinc concentrations.While femurs were removed from the surrounding muscles to measure bone mass density using the X-ray edge detection technique,then collected for histology and estrogen receptor(ER)immunohistochemistry.Results:Ovariectomy altered serum estrogen levels resulting in increased food intake and weight gain,while estrogen and EBN supplementation attenuated these changes.Ovariectomy also reduced bone ER expression and density,and the production of osteopcalcin and osteorotegerin,which are important pro-osteoplastic hormones that promote bone mineraliztion and density.Conversely,estrogen and EBN increased serum estrogen levels leading to increased bone ER expression,pro-osteoplastic hormone production and bone density(all P<0.05).Conclusion:EBN could be used as a safe alternative to hormone replacement therapys for managing menopausal complications like bone degeneration.展开更多
Light detection and ranging(LiDAR)sensors play a vital role in acquiring 3D point cloud data and extracting valuable information about objects for tasks such as autonomous driving,robotics,and virtual reality(VR).Howe...Light detection and ranging(LiDAR)sensors play a vital role in acquiring 3D point cloud data and extracting valuable information about objects for tasks such as autonomous driving,robotics,and virtual reality(VR).However,the sparse and disordered nature of the 3D point cloud poses significant challenges to feature extraction.Overcoming limitations is critical for 3D point cloud processing.3D point cloud object detection is a very challenging and crucial task,in which point cloud processing and feature extraction methods play a crucial role and have a significant impact on subsequent object detection performance.In this overview of outstanding work in object detection from the 3D point cloud,we specifically focus on summarizing methods employed in 3D point cloud processing.We introduce the way point clouds are processed in classical 3D object detection algorithms,and their improvements to solve the problems existing in point cloud processing.Different voxelization methods and point cloud sampling strategies will influence the extracted features,thereby impacting the final detection performance.展开更多
基金Supported by Grants from Ministry of Science,Technology and Innovation,E-science Fund(No.5450666)Malaysia+3 种基金the Health and Family Planning Commission of Hebei(No.20160315)the Administration of Traditional Chinese Medicine of Hebei(No.2017196)the Key Discipline Construction Project of Hebei Provincial Universities[No.JiJiao Gao-2013-(4)-2012-37]Start up Fund for High Level Talents of Chengde Medical University(No.201704)。
文摘Objective:To investigate the mechanistic basis for the attenuation of bone degeneration by edible bird's nest(EBN)in ovariectomized rats.Methods:Forty-two female Sprage-Dawley rats were randomized into 7 groups(6 in each group).The ovariectomized(OVX)and OVX+6%,3%,and 1.5%EBN and OVX+estrogen groups were given standard rat chow alone,standard rat chow+6%,3%,and 1.5%EBN,or standard rat chow+estrogen therapy(0.2mg/kg per day),respectively.The sham-operation group was surgically opened without removing the ovaries.The control group did not have any surgical intervention.After 12 weeks of intervention,blood samples were taken for serum estrogen,osteocalcin,and osteoprotegerin,as well as the measurement of magnesium,calcium abd zinc concentrations.While femurs were removed from the surrounding muscles to measure bone mass density using the X-ray edge detection technique,then collected for histology and estrogen receptor(ER)immunohistochemistry.Results:Ovariectomy altered serum estrogen levels resulting in increased food intake and weight gain,while estrogen and EBN supplementation attenuated these changes.Ovariectomy also reduced bone ER expression and density,and the production of osteopcalcin and osteorotegerin,which are important pro-osteoplastic hormones that promote bone mineraliztion and density.Conversely,estrogen and EBN increased serum estrogen levels leading to increased bone ER expression,pro-osteoplastic hormone production and bone density(all P<0.05).Conclusion:EBN could be used as a safe alternative to hormone replacement therapys for managing menopausal complications like bone degeneration.
文摘Light detection and ranging(LiDAR)sensors play a vital role in acquiring 3D point cloud data and extracting valuable information about objects for tasks such as autonomous driving,robotics,and virtual reality(VR).However,the sparse and disordered nature of the 3D point cloud poses significant challenges to feature extraction.Overcoming limitations is critical for 3D point cloud processing.3D point cloud object detection is a very challenging and crucial task,in which point cloud processing and feature extraction methods play a crucial role and have a significant impact on subsequent object detection performance.In this overview of outstanding work in object detection from the 3D point cloud,we specifically focus on summarizing methods employed in 3D point cloud processing.We introduce the way point clouds are processed in classical 3D object detection algorithms,and their improvements to solve the problems existing in point cloud processing.Different voxelization methods and point cloud sampling strategies will influence the extracted features,thereby impacting the final detection performance.
