Vascular cambium produces the phloem and xylem,vascular tissues that transport resources and provide mechanical support,making it an ideal target for crop improvement.However,much remains unknown about how vascular ca...Vascular cambium produces the phloem and xylem,vascular tissues that transport resources and provide mechanical support,making it an ideal target for crop improvement.However,much remains unknown about how vascular cambium proliferates.In this study,through pharmaceutical and genetic manipulation of reactive oxygen species(ROS)maxima,we demonstrate a direct link between levels of ROS and activity of LATERAL ORGAN BOUNDARIES DOMAIN 11(LBD11)in maintaining vascular cambium activity.LBD11 activates the transcriptionof several keyROS metabolic genes,including PEROXIDASE71and RESPIRATORY BURST OXIDASE HOMOLOGS D and F,to generate local ROS maxima in cambium,which in turn enhance the proliferation of cambial cells.In a negative feedback mechanism,higher Ros levels then repress LBD11 expression and maintain the balance of cambial cell proliferation.Our findings thus reveal the role of a novel LBD11/ROS-dependent feedback regulatory system in maintaining vascular cambiumspecific redox homeostasis and radial growth inplants.展开更多
The recent advances of wearable sensors are remarkable but there are still limitations that they need to be refabricated to tune the sensor for target signal.However,biological sensory systems have the inherent potent...The recent advances of wearable sensors are remarkable but there are still limitations that they need to be refabricated to tune the sensor for target signal.However,biological sensory systems have the inherent potential to adjust their sensitivity according to the external environment,allowing for a broad and enhanced detection.Here,we developed a Tunable,Ultrasensitive,Nature-inspired,Epidermal Sensor(TUNES)that the strain sensitivity was dramatically increased(GF~30k)and the pressure sensitivity could be tuned(10–254 kPa^(−1))by preset membrane tension.The sensor adjusts the sensitivity to the pressure regime by preset tension,so it can measure a wide range(0.05 Pa–25 kPa)with the best performance:from very small signals such as minute pulse to relatively large signals such as muscle contraction and respiration.We verified its capabilities as a wearable health monitoring system by clinical trial comparing with pressure wire which is considered the current gold standard of blood pressure(r=0.96)and home health care system by binary classification of Old’s/Young’s pulse waves via machine learning(accuracy 95%).展开更多
A superresolution imaging approach that localizes very small targets,such as red blood cells or droplets of injected photoacoustic dye,has significantly improved spatial resolution in various biological and medical im...A superresolution imaging approach that localizes very small targets,such as red blood cells or droplets of injected photoacoustic dye,has significantly improved spatial resolution in various biological and medical imaging modalities.However,this superior spatial resolution is achieved by sacrificing temporal resolution because many raw image frames,each containing the localization target,must be superimposed to form a sufficiently sampled high-density superresolution image.Here,we demonstrate a computational strategy based on deep neural networks(DNNs)to reconstruct high-density superresolution images from far fewer raw image frames.The localization strategy can be applied for both 3D label-free localization optical-resolution photoacoustic microscopy(OR-PAM)and 2D labeled localization photoacoustic computed tomography(PACT).For the former,the required number of raw volumetric frames is reduced from tens to fewer than ten.For the latter,the required number of raw 2D frames is reduced by 12 fold.Therefore,our proposed method has simultaneously improved temporal(via the DNN)and spatial(via the localization method)resolutions in both label-free microscopy and labeled tomography.Deep-learning powered localization PA imaging can potentially provide a practical tool in preclinical and clinical studies requiring fast temporal and fine spatial resolutions.展开更多
The digitized format of microstructures,or digital microstructures,plays a crucial role in modern-day materials research.Unfortunately,the acquisition of digital microstructures through experimental means can be unsuc...The digitized format of microstructures,or digital microstructures,plays a crucial role in modern-day materials research.Unfortunately,the acquisition of digital microstructures through experimental means can be unsuccessful in delivering sufficient resolution that is necessary to capture all relevant geometric features of the microstructures.The resolution-sensitive microstructural features overlooked due to insufficient resolution may limit one’s ability to conduct a thorough microstructure characterization and material behavior analysis such as mechanical analysis based on numerical modeling.Here,a highly efficient super-resolution imaging based on deep learning is developed using a deep super-resolution residual network to super-resolved low-resolution(LR)microstructure data for microstructure characterization and finite element(FE)mechanical analysis.Microstructure characterization and FE model based mechanical analysis using the super-resolved microstructure data not only proved to be as accurate as those based on high-resolution(HR)data but also provided insights on local microstructural features such as grain boundary normal and local stress distribution,which can be only partially considered or entirely disregarded in LR data-based analysis.展开更多
Integration of internal and external cues into developmental programs is indispensable for growth and development of plants, which involve complex interplays among signaling pathways activated by the internal and exte...Integration of internal and external cues into developmental programs is indispensable for growth and development of plants, which involve complex interplays among signaling pathways activated by the internal and external factors (IEFs). However, decoding these complex interplays is still challenging. Here, we present a web-based platform that identifies key regulators and Network models delineating Interplays among Developmental signaling (iNID) in Arabidopsis. iNID provides a comprehensive resource of (1) transcriptomes previously collected under the conditions treated with a broad spectrum of IEFs and (2) protein and genetic interactome data in Arabidopsis. In addition, iNID provides an array of tools for identifying key regulators and network models related to interplays among IEFs using transcriptome and interactome data. To demonstrate the utility of iNID, we investigated the interplays of (1) phytohormones and light and (2) phytohormones and biotic stresses. The results revealed 34 potential regulators of the interplays, some of which have not been reported in association with the interplays, and also network models that delineate the involvement of the 34 regulators in the interplays, providing novel insights into the interplays collectively defined by phytohormones, light, and biotic stresses. We then experimentally verified that BME3 and TEM1, among the selected regulators, are involved in the auxin-brassinosteroid (BR)-blue light interplay. Therefore, iNID serves as a useful tool to provide a basis for understanding interplays among IEFs.展开更多
基金grants to I.H.from the New Breeding Technologies Development Program funded by the Rural Development Administration,Republic of Korea(project no.PJ016538)from the National Research Foundation of Korea(NRF)grant funded by the Ministry of Science and ICT,Republic of Korea(project no.2020R1A2C3012750)+1 种基金Brain Pool Program through the NRF funded by the Ministry of Science and ICT(grant no.2017H1D3A1A03055171)Basic Science Research Program through the NRF funded by the Ministry of Education(grant no.2019R1/1A1A01055449).
文摘Vascular cambium produces the phloem and xylem,vascular tissues that transport resources and provide mechanical support,making it an ideal target for crop improvement.However,much remains unknown about how vascular cambium proliferates.In this study,through pharmaceutical and genetic manipulation of reactive oxygen species(ROS)maxima,we demonstrate a direct link between levels of ROS and activity of LATERAL ORGAN BOUNDARIES DOMAIN 11(LBD11)in maintaining vascular cambium activity.LBD11 activates the transcriptionof several keyROS metabolic genes,including PEROXIDASE71and RESPIRATORY BURST OXIDASE HOMOLOGS D and F,to generate local ROS maxima in cambium,which in turn enhance the proliferation of cambial cells.In a negative feedback mechanism,higher Ros levels then repress LBD11 expression and maintain the balance of cambial cell proliferation.Our findings thus reveal the role of a novel LBD11/ROS-dependent feedback regulatory system in maintaining vascular cambiumspecific redox homeostasis and radial growth inplants.
基金supported by funding from NRF of Korea(grant no.2019R1H1A1080221,2019R1F1A1063066,2019R1C1C1007629,2021R1A6A3A01087289,2021R1A6A3A13045869,2022R1A2C2093100,2022R1A6A3A13071489)supported by Korea Environment Industry&Technology Institute(KEITI)through Digital Infrastructure Building Project for Monitoring,Surveying,and Evaluating the Environmental Health Program,funded by Korea Ministry of Environment(MOE)(2021003330009)supported by a grant of the Basic Research Program funded by the Korea Institute of Machinery and Materials(grant number:NK231A).
文摘The recent advances of wearable sensors are remarkable but there are still limitations that they need to be refabricated to tune the sensor for target signal.However,biological sensory systems have the inherent potential to adjust their sensitivity according to the external environment,allowing for a broad and enhanced detection.Here,we developed a Tunable,Ultrasensitive,Nature-inspired,Epidermal Sensor(TUNES)that the strain sensitivity was dramatically increased(GF~30k)and the pressure sensitivity could be tuned(10–254 kPa^(−1))by preset membrane tension.The sensor adjusts the sensitivity to the pressure regime by preset tension,so it can measure a wide range(0.05 Pa–25 kPa)with the best performance:from very small signals such as minute pulse to relatively large signals such as muscle contraction and respiration.We verified its capabilities as a wearable health monitoring system by clinical trial comparing with pressure wire which is considered the current gold standard of blood pressure(r=0.96)and home health care system by binary classification of Old’s/Young’s pulse waves via machine learning(accuracy 95%).
基金This research was supported by Basic Science Research Program through the National Research Foundation of Korea(NRF),funded by the Ministry of Education(2020R1A6A1A03047902)supported by National R&D Program through the NRF funded by the Ministry of Science and ICT(MSIT)(2020M3H2A1078045)+4 种基金supported by the NRF grant funded by the Korea government MSIT(No.NRF-2019R1A2C2006269 and No.2020R1C1C1013549)This work was partly supported by the Institute of Information&communications Technology Planning&Evaluation(ITP)grant funded by the Korea government MSIT(No.2019-0-01906,Artificial Intelligence Graduate School Program(POSTECH))Korea Evaluation Institute of Industrial Technology(KEIT)grant funded by the Ministry of Trade,industry and Energy(MOTIE)This work was also supported by the Korea Medical Device Development Fund grant funded by the MOTIE(9991007019,KMDF_PR_20200901_0008)It was also supported by the BK21 Four project.
文摘A superresolution imaging approach that localizes very small targets,such as red blood cells or droplets of injected photoacoustic dye,has significantly improved spatial resolution in various biological and medical imaging modalities.However,this superior spatial resolution is achieved by sacrificing temporal resolution because many raw image frames,each containing the localization target,must be superimposed to form a sufficiently sampled high-density superresolution image.Here,we demonstrate a computational strategy based on deep neural networks(DNNs)to reconstruct high-density superresolution images from far fewer raw image frames.The localization strategy can be applied for both 3D label-free localization optical-resolution photoacoustic microscopy(OR-PAM)and 2D labeled localization photoacoustic computed tomography(PACT).For the former,the required number of raw volumetric frames is reduced from tens to fewer than ten.For the latter,the required number of raw 2D frames is reduced by 12 fold.Therefore,our proposed method has simultaneously improved temporal(via the DNN)and spatial(via the localization method)resolutions in both label-free microscopy and labeled tomography.Deep-learning powered localization PA imaging can potentially provide a practical tool in preclinical and clinical studies requiring fast temporal and fine spatial resolutions.
基金This study was supported by the Fundamental Research Program(No.PNK7760)of the Korea Institute of Materials Science,Brain Korea 21 PLUS project for Center for Creative Industrial Materials(F16SN25D1706)the Future Material Discovery Project of the National Research Foundation of Korea(NRF)funded by the Ministry of Science and ICT of Korea(NRF-2016M3D1A1023383)+2 种基金the NRF grant funded by the Korea government(MSIP)(NRF-2021R1A2C3006662)the NRF grant funded by the Korea Government(MSIT)(No.2020R1A2C1009744)Institute for Information communications Technology Promotion(IITP)grant funded by the Korea government(MSIP)(No.2019-0-01906,Artificial Intelligence Graduate School Program(POSTECH)).
文摘The digitized format of microstructures,or digital microstructures,plays a crucial role in modern-day materials research.Unfortunately,the acquisition of digital microstructures through experimental means can be unsuccessful in delivering sufficient resolution that is necessary to capture all relevant geometric features of the microstructures.The resolution-sensitive microstructural features overlooked due to insufficient resolution may limit one’s ability to conduct a thorough microstructure characterization and material behavior analysis such as mechanical analysis based on numerical modeling.Here,a highly efficient super-resolution imaging based on deep learning is developed using a deep super-resolution residual network to super-resolved low-resolution(LR)microstructure data for microstructure characterization and finite element(FE)mechanical analysis.Microstructure characterization and FE model based mechanical analysis using the super-resolved microstructure data not only proved to be as accurate as those based on high-resolution(HR)data but also provided insights on local microstructural features such as grain boundary normal and local stress distribution,which can be only partially considered or entirely disregarded in LR data-based analysis.
文摘Integration of internal and external cues into developmental programs is indispensable for growth and development of plants, which involve complex interplays among signaling pathways activated by the internal and external factors (IEFs). However, decoding these complex interplays is still challenging. Here, we present a web-based platform that identifies key regulators and Network models delineating Interplays among Developmental signaling (iNID) in Arabidopsis. iNID provides a comprehensive resource of (1) transcriptomes previously collected under the conditions treated with a broad spectrum of IEFs and (2) protein and genetic interactome data in Arabidopsis. In addition, iNID provides an array of tools for identifying key regulators and network models related to interplays among IEFs using transcriptome and interactome data. To demonstrate the utility of iNID, we investigated the interplays of (1) phytohormones and light and (2) phytohormones and biotic stresses. The results revealed 34 potential regulators of the interplays, some of which have not been reported in association with the interplays, and also network models that delineate the involvement of the 34 regulators in the interplays, providing novel insights into the interplays collectively defined by phytohormones, light, and biotic stresses. We then experimentally verified that BME3 and TEM1, among the selected regulators, are involved in the auxin-brassinosteroid (BR)-blue light interplay. Therefore, iNID serves as a useful tool to provide a basis for understanding interplays among IEFs.