Cellular mechanotransduction characterized by the transformation of mechanical stimuli into biochemical signals,represents a pivotal and complex process underpinning a multitude of cellular functionalities.This proces...Cellular mechanotransduction characterized by the transformation of mechanical stimuli into biochemical signals,represents a pivotal and complex process underpinning a multitude of cellular functionalities.This process is integral to diverse biological phenomena,including embryonic development,cell migration,tissue regeneration,and disease pathology,particularly in the context of cancer metastasis and cardiovascular diseases.Despite the profound biological and clinical significance of mechanotransduction,our understanding of this complex process remains incomplete.The recent development of advanced optical techniques enables in-situ force measurement and subcellular manipulation from the outer cell membrane to the organelles inside a cell.In this review,we delved into the current state-of-the-art techniques utilized to probe cellular mechanobiology,their principles,applications,and limitations.We mainly examined optical methodologies to quantitatively measure the mechanical properties of cells during intracellular transport,cell adhesion,and migration.We provided an introductory overview of various conventional and optical-based techniques for probing cellular mechanics.These techniques have provided into the dynamics of mechanobiology,their potential to unravel mechanistic intricacies and implications for therapeutic intervention.展开更多
Autonomous driving technology has made a lot of outstanding achievements with deep learning,and the vehicle detection and classification algorithm has become one of the critical technologies of autonomous driving syst...Autonomous driving technology has made a lot of outstanding achievements with deep learning,and the vehicle detection and classification algorithm has become one of the critical technologies of autonomous driving systems.The vehicle instance segmentation can perform instance-level semantic parsing of vehicle information,which is more accurate and reliable than object detection.However,the existing instance segmentation algorithms still have the problems of poor mask prediction accuracy and low detection speed.Therefore,this paper proposes an advanced real-time instance segmentation model named FIR-YOLACT,which fuses the ICIoU(Improved Complete Intersection over Union)and Res2Net for the YOLACT algorithm.Specifically,the ICIoU function can effectively solve the degradation problem of the original CIoU loss function,and improve the training convergence speed and detection accuracy.The Res2Net module fused with the ECA(Efficient Channel Attention)Net is added to the model’s backbone network,which improves the multi-scale detection capability and mask prediction accuracy.Furthermore,the Cluster NMS(Non-Maximum Suppression)algorithm is introduced in the model’s bounding box regression to enhance the performance of detecting similarly occluded objects.The experimental results demonstrate the superiority of FIR-YOLACT to the based methods and the effectiveness of all components.The processing speed reaches 28 FPS,which meets the demands of real-time vehicle instance segmentation.展开更多
Tumor cells progressively remodel cytoskeletal structures and reduce cellular stiffness during tumor progression,implicating the correlation between cell mechanics and malignancy.However,the roles of tumor cell cytosk...Tumor cells progressively remodel cytoskeletal structures and reduce cellular stiffness during tumor progression,implicating the correlation between cell mechanics and malignancy.However,the roles of tumor cell cytoskeleton and the mechanics in tumor progression remain incompletely understood.We report that softening/stiffening tumor cells by targeting actomyosin promotes/suppresses self-renewal in vitro and tumorigenic potential in vivo.Weakening/strengthening actin cytoskeleton impairs/reinforces the interaction between adenomatous polyposis coli(APC)andβ-catenin,which facilitatesβ-catenin nuclear/cytoplasmic localization.Nuclearβ-catenin binds to the promoter of Oct4,which enhances its transcription that is crucial in sustaining self-renewal and malignancy.These results demonstrate that the mechanics of tumor cells dictate self-renewal through cytoskeleton-APC-Wnt/β-catenin-Oct4 signaling,which are correlated with tumor differentiation and patient survival.This study unveils an uncovered regulatory role of cell mechanics in self-renewal and malignancy,and identifies tumor cell mechanics as a hallmark not only for cancer diagnosis but also for mechanotargeting.展开更多
基金the funding from Start-up Fundings of Ocean University of China(862401013154 and 862401013155)Laboratory for Marine Drugs and Bioproducts Qingdao Marine Science and Technology Center(LMDBCXRC202401 and LMDBCXRC202402)+1 种基金Taishan Scholar Youth Expert Program of Shandong Province(tsqn202306102 and tsqn202312105)Shandong Provincial Overseas Excellent Young Scholar Program(2024HWYQ-042 and 2024HWYQ-043)for supporting this work.
文摘Cellular mechanotransduction characterized by the transformation of mechanical stimuli into biochemical signals,represents a pivotal and complex process underpinning a multitude of cellular functionalities.This process is integral to diverse biological phenomena,including embryonic development,cell migration,tissue regeneration,and disease pathology,particularly in the context of cancer metastasis and cardiovascular diseases.Despite the profound biological and clinical significance of mechanotransduction,our understanding of this complex process remains incomplete.The recent development of advanced optical techniques enables in-situ force measurement and subcellular manipulation from the outer cell membrane to the organelles inside a cell.In this review,we delved into the current state-of-the-art techniques utilized to probe cellular mechanobiology,their principles,applications,and limitations.We mainly examined optical methodologies to quantitatively measure the mechanical properties of cells during intracellular transport,cell adhesion,and migration.We provided an introductory overview of various conventional and optical-based techniques for probing cellular mechanics.These techniques have provided into the dynamics of mechanobiology,their potential to unravel mechanistic intricacies and implications for therapeutic intervention.
基金supported by the Natural Science Foundation of Guizhou Province(Grant Number:20161054)Joint Natural Science Foundation of Guizhou Province(Grant Number:LH20177226)+1 种基金2017 Special Project of New Academic Talent Training and Innovation Exploration of Guizhou University(Grant Number:20175788)The National Natural Science Foundation of China under Grant No.12205062.
文摘Autonomous driving technology has made a lot of outstanding achievements with deep learning,and the vehicle detection and classification algorithm has become one of the critical technologies of autonomous driving systems.The vehicle instance segmentation can perform instance-level semantic parsing of vehicle information,which is more accurate and reliable than object detection.However,the existing instance segmentation algorithms still have the problems of poor mask prediction accuracy and low detection speed.Therefore,this paper proposes an advanced real-time instance segmentation model named FIR-YOLACT,which fuses the ICIoU(Improved Complete Intersection over Union)and Res2Net for the YOLACT algorithm.Specifically,the ICIoU function can effectively solve the degradation problem of the original CIoU loss function,and improve the training convergence speed and detection accuracy.The Res2Net module fused with the ECA(Efficient Channel Attention)Net is added to the model’s backbone network,which improves the multi-scale detection capability and mask prediction accuracy.Furthermore,the Cluster NMS(Non-Maximum Suppression)algorithm is introduced in the model’s bounding box regression to enhance the performance of detecting similarly occluded objects.The experimental results demonstrate the superiority of FIR-YOLACT to the based methods and the effectiveness of all components.The processing speed reaches 28 FPS,which meets the demands of real-time vehicle instance segmentation.
基金support from the National Natural Science Foundation of China(project no.11972316)Shenzhen Science and Technology Innovation Commission(project nos.JCYJ20200109142001798,SGDX2020110309520303,and JCYJ20220531091002006)+3 种基金General Research Fund of Hong Kong Research Grant Council(PolyU 15214320)Health and Medical Research Fund(HMRF18191421)the Research Institute for Smart Ageing in Hong Kong Polytechnic University(1-CD75)Hong Kong Polytechnic University(1-ZE2M,1-ZVY1).
文摘Tumor cells progressively remodel cytoskeletal structures and reduce cellular stiffness during tumor progression,implicating the correlation between cell mechanics and malignancy.However,the roles of tumor cell cytoskeleton and the mechanics in tumor progression remain incompletely understood.We report that softening/stiffening tumor cells by targeting actomyosin promotes/suppresses self-renewal in vitro and tumorigenic potential in vivo.Weakening/strengthening actin cytoskeleton impairs/reinforces the interaction between adenomatous polyposis coli(APC)andβ-catenin,which facilitatesβ-catenin nuclear/cytoplasmic localization.Nuclearβ-catenin binds to the promoter of Oct4,which enhances its transcription that is crucial in sustaining self-renewal and malignancy.These results demonstrate that the mechanics of tumor cells dictate self-renewal through cytoskeleton-APC-Wnt/β-catenin-Oct4 signaling,which are correlated with tumor differentiation and patient survival.This study unveils an uncovered regulatory role of cell mechanics in self-renewal and malignancy,and identifies tumor cell mechanics as a hallmark not only for cancer diagnosis but also for mechanotargeting.
