The human pose paradigm is estimated using a transformer-based multi-branch multidimensional directed the three-dimensional(3D)method that takes into account self-occlusion,badly posedness,and a lack of depth data in ...The human pose paradigm is estimated using a transformer-based multi-branch multidimensional directed the three-dimensional(3D)method that takes into account self-occlusion,badly posedness,and a lack of depth data in the per-frame 3D posture estimation from two-dimensional(2D)mapping to 3D mapping.Firstly,by examining the relationship between the movements of different bones in the human body,four virtual skeletons are proposed to enhance the cyclic constraints of limb joints.Then,multiple parameters describing the skeleton are fused and projected into a high-dimensional space.Utilizing a multi-branch network,motion features between bones and overall motion features are extracted to mitigate the drift error in the estimation results.Furthermore,the estimated relative depth is projected into 3D space,and the error is calculated against real 3D data,forming a loss function along with the relative depth error.This article adopts the average joint pixel error as the primary performance metric.Compared to the benchmark approach,the estimation findings indicate an increase in average precision of 1.8 mm within the Human3.6M sample.展开更多
BACKGROUND Trastuzumab-targeted therapy is currently the standard of care for advanced human epidermal growth factor receptor 2(HER2)-positive gastric cancer.However,the emergence of resistance to trastuzumab poses si...BACKGROUND Trastuzumab-targeted therapy is currently the standard of care for advanced human epidermal growth factor receptor 2(HER2)-positive gastric cancer.However,the emergence of resistance to trastuzumab poses significant challenges.AIM To identify the key genes associated with trastuzumab resistance.These results provide a basis for the development of interventions to address drug resistance and improve patient outcomes.METHODS High-throughput sequencing and bioinformatics were used to identify the differentially expressed pivotal gene BIRC3 and delineate its potential function and pathway regulation.Tumor samples were collected from patients with HER2-positive gastric cancer to evaluate the correlation between BIRC3 expression and trastuzumab resistance.We established gastric cancer cell lines with both highly expressed and suppressed levels of BIRC3,followed by comprehensive in vitro and in vivo experiments to confirm the involvement of BIRC3 in trastuzumab resistance and to elucidate its underlying mechanisms.RESULTS In patients with HER2-positive gastric cancer,there is a significant correlation between elevated BIRC3 expression in tumor tissues and higher T stage,tumor node metastasis stage,as well as poor overall survival and progressionfree survival.BIRC3 is highly expressed in trastuzumab-resistant gastric cancer cell lines,where it inhibits tumor cell apoptosis and enhances trastuzumab resistance by promoting the phosphorylation and activation of the phosphoinositide 3-kinase-Akt(PI3K-AKT)pathway in HER2-positive gastric cancer cells,both in vivo and in vitro.CONCLUSION This study revealed a robust association between high BIRC3 expression and an unfavorable prognosis in patients with HER2-positive gastric cancer.Thus,the high expression of BIRC3 stimulated PI3K-AKT phosphorylation and activation,stimulating the proliferation of HER2-positive tumor cells and suppressing apoptosis,ultimately leading to trastuzumab resistance.展开更多
Background Intelligent garments,a burgeoning class of wearable devices,have extensive applications in domains such as sports training and medical rehabilitation.Nonetheless,existing research in the smart wearables dom...Background Intelligent garments,a burgeoning class of wearable devices,have extensive applications in domains such as sports training and medical rehabilitation.Nonetheless,existing research in the smart wearables domain predominantly emphasizes sensor functionality and quantity,often skipping crucial aspects related to user experience and interaction.Methods To address this gap,this study introduces a novel real-time 3D interactive system based on intelligent garments.The system utilizes lightweight sensor modules to collect human motion data and introduces a dual-stream fusion network based on pulsed neural units to classify and recognize human movements,thereby achieving real-time interaction between users and sensors.Additionally,the system incorporates 3D human visualization functionality,which visualizes sensor data and recognizes human actions as 3D models in real time,providing accurate and comprehensive visual feedback to help users better understand and analyze the details and features of human motion.This system has significant potential for applications in motion detection,medical monitoring,virtual reality,and other fields.The accurate classification of human actions contributes to the development of personalized training plans and injury prevention strategies.Conclusions This study has substantial implications in the domains of intelligent garments,human motion monitoring,and digital twin visualization.The advancement of this system is expected to propel the progress of wearable technology and foster a deeper comprehension of human motion.展开更多
3D human pose estimation is a major focus area in the field of computer vision,which plays an important role in practical applications.This article summarizes the framework and research progress related to the estimat...3D human pose estimation is a major focus area in the field of computer vision,which plays an important role in practical applications.This article summarizes the framework and research progress related to the estimation of monocular RGB images and videos.An overall perspective ofmethods integrated with deep learning is introduced.Novel image-based and video-based inputs are proposed as the analysis framework.From this viewpoint,common problems are discussed.The diversity of human postures usually leads to problems such as occlusion and ambiguity,and the lack of training datasets often results in poor generalization ability of the model.Regression methods are crucial for solving such problems.Considering image-based input,the multi-view method is commonly used to solve occlusion problems.Here,the multi-view method is analyzed comprehensively.By referring to video-based input,the human prior knowledge of restricted motion is used to predict human postures.In addition,structural constraints are widely used as prior knowledge.Furthermore,weakly supervised learningmethods are studied and discussed for these two types of inputs to improve the model generalization ability.The problem of insufficient training datasets must also be considered,especially because 3D datasets are usually biased and limited.Finally,emerging and popular datasets and evaluation indicators are discussed.The characteristics of the datasets and the relationships of the indicators are explained and highlighted.Thus,this article can be useful and instructive for researchers who are lacking in experience and find this field confusing.In addition,by providing an overview of 3D human pose estimation,this article sorts and refines recent studies on 3D human pose estimation.It describes kernel problems and common useful methods,and discusses the scope for further research.展开更多
BACKGROUND： Many methods have been attempted to repair nerves following spinal cord injury, including peripheral nerve transplantation, Schwann cell transplantation, olfactory ensheathing cell transplantation, and em...BACKGROUND： Many methods have been attempted to repair nerves following spinal cord injury, including peripheral nerve transplantation, Schwann cell transplantation, olfactory ensheathing cell transplantation, and embryonic neural tissue transplantation. However, there is a need for improved outcomes. OBJECTIVE： To investigate the repair feasibility for rat spinal cord injury using human neural stem cells （hNSCs） genetically modified by lentivirus to express neurotrophin-3. DESIGN, TIME AND SETTING： In vitro cell biological experiment and in vivo randomized, controlled genetic engineering experiment were performed at the Third Military Medical University of Chinese PLA and First People＇s Hospital of Yibin, China from March 2006 to December 2007. MATERIALS： A total of 64 adult, female, Wistar rats were used for the in vivo study. Of them, 48 rats were used to establish models of spinal cord hemisection, and were subsequently equally and randomly assigned to model, genetically modified hNSC, and normal hNSC groups. The remaining 16 rats served as normal controls. METHODS： hNSCs were in vitro genetically modified by lentivirus to secrete both green fluorescence protein and neurotrophin-3. Neurotrophin-3 expression was measured by Western blot. Genetically modified hNSC or normal hNSC suspension （5 × 10^5） was injected into the rat spinal cord following T10 spinal cord hemisection. A total of 5μL Dulbecco＇s-modified Eagle＇s medium was infused into the rat spinal cord in the model grop. Transgene expression and survival of transplanted hNSCs were determined by immunohistochemistry. Motor function was evaluated using the Basso, Beattie, and Bresnahan （BBB） scale. MAIN OUTCOME MEASURES： The following parameters were measured： expression of neurotrophin-3 produced by genetically modified hNSCs, transgene expression and survival of hNSCs in rats, motor function in rats. RESULTS： hNSCs were successfully genetically modified by lentivirus to stably express neurotrophin-3. The transplanted hNSCs primarily gathered at, or around, the injection site two weeks following transplantation, and gradually migrated towards the surrounding tissue. Transplanted hNSCs were observed 7.0-8.0 mm away from the injection site. In addition, hNSCs were observed 10 weeks after transplantation. At week 4, BBB locomotor scores were significantly greater in the genetically modified hNSC and normal hNSC groups, compared with the model group （P 〈 0.05）, and scores were significantly greater in the genetically modified hNSC group compared with the normal hNSC group （P 〈 0.05）. CONCLUSION： hNSCs were genetically modified with lentivirus to stably secrete neurotrophin-3. hNSCs improved motor function recovery in rats following spinal cord injury.展开更多
With the advancement of image sensing technology, estimating 3Dhuman pose frommonocular video has becomea hot research topic in computer vision. 3D human pose estimation is an essential prerequisite for subsequentacti...With the advancement of image sensing technology, estimating 3Dhuman pose frommonocular video has becomea hot research topic in computer vision. 3D human pose estimation is an essential prerequisite for subsequentaction analysis and understanding. It empowers a wide spectrum of potential applications in various areas, suchas intelligent transportation, human-computer interaction, and medical rehabilitation. Currently, some methodsfor 3D human pose estimation in monocular video employ temporal convolutional network (TCN) to extractinter-frame feature relationships, but the majority of them suffer from insufficient inter-frame feature relationshipextractions. In this paper, we decompose the 3D joint location regression into the bone direction and length, wepropose the TCG, a temporal convolutional network incorporating Gaussian error linear units (GELU), to solvebone direction. It enablesmore inter-frame features to be captured andmakes the utmost of the feature relationshipsbetween data. Furthermore, we adopt kinematic structural information to solve bone length enhancing the use ofintra-frame joint features. Finally, we design a loss function for joint training of the bone direction estimationnetwork with the bone length estimation network. The proposed method has extensively experimented on thepublic benchmark dataset Human3.6M. Both quantitative and qualitative experimental results showed that theproposed method can achieve more accurate 3D human pose estimations.展开更多
3-dimension(3-D)printing technology is growing strongly with many applications,one of which is the garment industry.The application of human body models to the garment industry is necessary to respond to the increasin...3-dimension(3-D)printing technology is growing strongly with many applications,one of which is the garment industry.The application of human body models to the garment industry is necessary to respond to the increasing personalization demand and still guarantee aesthetics.This paper proposes amethod to construct 3-D human models by applying deep learning.We calculate the location of the main slices of the human body,including the neck,chest,belly,buttocks,and the rings of the extremities,using pre-existing information.Then,on the positioning frame,we find the key points(fixed and unaltered)of these key slices and update these points tomatch the current parameters.To add points to a star slice,we use a deep learning model tomimic the form of the human body at that slice position.We use interpolation to produce sub-slices of different body sections based on the main slices to create complete body parts morphologically.We combine all slices to construct a full 3-D representation of the human body.展开更多
Purpose: Patient-specific quality assurance (PSQA) requires manual operation of different workstations, which is time-consuming and error-prone. Therefore, developing automated solutions to improve efficiency and accu...Purpose: Patient-specific quality assurance (PSQA) requires manual operation of different workstations, which is time-consuming and error-prone. Therefore, developing automated solutions to improve efficiency and accuracy is a priority. The purpose of this study was to develop a general software interface with scripting on a human interactive device (HID) for improving the efficiency and accuracy of manual quality assurance (QA) procedures. Methods: As an initial application, we aimed to automate our PSQA workflow that involves Varian Eclipse treatment planning system, Elekta MOSAIQ oncology information system and PTW Verisoft application. A general platform, the AutoFrame interface with two imbedded subsystems—the AutoFlow and the PyFlow, was developed with a scripting language for automating human operations of aforementioned systems. The interface included three functional modules: GUI module, UDF script interpreter and TCP/IP communication module. All workstations in the PSQA process were connected, and most manual operations were automated by AutoFrame sequentially or in parallel. Results: More than 20 PSQA tasks were performed both manually and using the developed AutoFrame interface. On average, 175 (±12) manual operations of the PSQA procedure were eliminated and performed by the automated process. The time to complete a PSQA task was 8.23 (±0.78) minutes for the automated workflow, in comparison to 13.91 (±3.01) minutes needed for manual operations. Conclusion: We have developed the AutoFrame interface framework that successfully automated our PSQA procedure, and significantly reduced the time, human (control/clicking/typing) errors, and operators’ stress. Future work will focus on improving the system’s flexibility and stability and extending its operations to other QA procedures.展开更多
Neurotrophin-3 （NT-3） can promote the repair of central nervous system and retinal damage. In previous reports, NT-3 has been expressed by viral vectors. However, plasmid vectors have a safer profile compared with v...Neurotrophin-3 （NT-3） can promote the repair of central nervous system and retinal damage. In previous reports, NT-3 has been expressed by viral vectors. However, plasmid vectors have a safer profile compared with viral vectors in clinical studies. This study recombined amplified human retinal NT-3 with a eukaryotic expression plasmid containing green fluorescent protein （GFP） to construct an NT-3 expression plasmid, pEGFP-N1-NT-3. The transfection efficiency 48 hours after pEGFP-N1-NT-3 transfection to 293T cells was 50.06 ＋ 2.78%. Abundant NTo3-GFP was expressed in 293T cells as observed by fluorescence microscopy, suggesting the construct pEGFP-N1-NT-3 effectively expressed and secreted NT-3-GFP. Secretory vesicles containing NT-3-GFP were observed in a constant location in cells by laser scan confocal microscopy, indicating the expression and secretion processes of NT-3 in eukaryotic cells were in accordance with the physical synthesis processes of secreted proteins. Western blot assay showed that pro-NTo3-GFP had a molecular weight of 56 kDa, further confirming NT-3-GFP expression. At 48 hours after transfection, the concentration of NT-3 in culture medium was 22.3 ng/mL, suggesting NT-3 produced by pEGFP-N1-NT-3 was efficiently secreted. This study constructed a human retinal-derived NT-3 eukaryotic expression plasmid that efficiently expressed and secreted NT-3.展开更多
BACKGROUND： Cell culture in vitro trials have demonstrated that neurotrophin-3 （NT-3） can enhance the survival of sensory neurons and sympathetic neurons, and can also support embryo-derived motor neurons. This eff...BACKGROUND： Cell culture in vitro trials have demonstrated that neurotrophin-3 （NT-3） can enhance the survival of sensory neurons and sympathetic neurons, and can also support embryo-derived motor neurons. This effect is dependent on nerve growth factor on the surface of cells. Understanding the role of NT-3 and its receptor in the early development of human embryonic brains will help to investigate the correlation between early survival of nerve cells and the microenvironment of neural regeneration. OBJECTIVE： To observe the proliferation of cerebral neurons in the development of human embryonic brain, and to investigate the location, expression and distribution of NT-3 and its receptor TrkC during human brain development. DESIGN, TIME AND SETTING： An observation study on cells was performed in the Department of ttuman Anatomy, Histology and Embryology, Chengdu Medical College in September 2007. MATERIALS： Fifteen specimens of flesh human embryo, aged 6 weeks, were used in this study. METHODS： The proliferation of cerebral neurons was detected using proliferating cell nuclear antigen, and the immunocytochemistry ABC technique was applied to observe the location, expression and distribution of NT-3 and its receptor TrkC in the brain of the human embryo. MAIN OUTCOME MEASURES： Location, expression and distribution of NT-3 and its receptor in the brain of the human embryo. RESULTS： In the early period （aged 6 weeks） of human embryonic development, proliferating cell nuclear antigen-positive reactive substances were mainly observed in the nucleus of the forebrain ventricular zone and subventricular zone, and the intensity was stronger in the subventricular zone than the forebrain ventricle. NT-3 positive reactive substance was mainly distributed in the cytoblastema of the forebrain neuroepithelial layer and nerve cell process, while TrkC was mainly distributed in the cell membrane of the forebrain ventricular zone and subventricular zone. During embryonic development, NT-3 and TrkC showed a positive immune reaction to a greater or lesser extent in ependymal epithelium. CONCLUSION： During early human embryonic development, cerebral nerve cells proliferate in the ventricular zone and subventricular zone, and NT-3 is expressed in the neural axon. The results show that the highly expressed NT-3 could promote the proliferation of neural axons and maintain the neuron body＇s survival.展开更多
基金supported by the Medical Special Cultivation Project of Anhui University of Science and Technology(Grant No.YZ2023H2B013)the Anhui Provincial Key Research and Development Project(Grant No.2022i01020015)the Open Project of Key Laboratory of Conveyance Equipment(East China Jiaotong University),Ministry of Education(KLCE2022-01).
文摘The human pose paradigm is estimated using a transformer-based multi-branch multidimensional directed the three-dimensional(3D)method that takes into account self-occlusion,badly posedness,and a lack of depth data in the per-frame 3D posture estimation from two-dimensional(2D)mapping to 3D mapping.Firstly,by examining the relationship between the movements of different bones in the human body,four virtual skeletons are proposed to enhance the cyclic constraints of limb joints.Then,multiple parameters describing the skeleton are fused and projected into a high-dimensional space.Utilizing a multi-branch network,motion features between bones and overall motion features are extracted to mitigate the drift error in the estimation results.Furthermore,the estimated relative depth is projected into 3D space,and the error is calculated against real 3D data,forming a loss function along with the relative depth error.This article adopts the average joint pixel error as the primary performance metric.Compared to the benchmark approach,the estimation findings indicate an increase in average precision of 1.8 mm within the Human3.6M sample.
文摘BACKGROUND Trastuzumab-targeted therapy is currently the standard of care for advanced human epidermal growth factor receptor 2(HER2)-positive gastric cancer.However,the emergence of resistance to trastuzumab poses significant challenges.AIM To identify the key genes associated with trastuzumab resistance.These results provide a basis for the development of interventions to address drug resistance and improve patient outcomes.METHODS High-throughput sequencing and bioinformatics were used to identify the differentially expressed pivotal gene BIRC3 and delineate its potential function and pathway regulation.Tumor samples were collected from patients with HER2-positive gastric cancer to evaluate the correlation between BIRC3 expression and trastuzumab resistance.We established gastric cancer cell lines with both highly expressed and suppressed levels of BIRC3,followed by comprehensive in vitro and in vivo experiments to confirm the involvement of BIRC3 in trastuzumab resistance and to elucidate its underlying mechanisms.RESULTS In patients with HER2-positive gastric cancer,there is a significant correlation between elevated BIRC3 expression in tumor tissues and higher T stage,tumor node metastasis stage,as well as poor overall survival and progressionfree survival.BIRC3 is highly expressed in trastuzumab-resistant gastric cancer cell lines,where it inhibits tumor cell apoptosis and enhances trastuzumab resistance by promoting the phosphorylation and activation of the phosphoinositide 3-kinase-Akt(PI3K-AKT)pathway in HER2-positive gastric cancer cells,both in vivo and in vitro.CONCLUSION This study revealed a robust association between high BIRC3 expression and an unfavorable prognosis in patients with HER2-positive gastric cancer.Thus,the high expression of BIRC3 stimulated PI3K-AKT phosphorylation and activation,stimulating the proliferation of HER2-positive tumor cells and suppressing apoptosis,ultimately leading to trastuzumab resistance.
基金Supported by the National Natural Science Foundation of China (62202346)Hubei Key Research and Development Program (2021BAA042)+3 种基金Open project of Engineering Research Center of Hubei Province for Clothing Information (2022HBCI01)Wuhan Applied Basic Frontier Research Project (2022013988065212)MIIT′s AI Industry Innovation Task Unveils Flagship Projects (Key Technologies,Equipment,and Systems for Flexible Customized and Intelligent Manufacturing in the Clothing Industry)Hubei Science and Technology Project of Safe Production Special Fund (Scene Control Platform Based on Proprioception Information Computing of Artificial Intelligence)。
文摘Background Intelligent garments,a burgeoning class of wearable devices,have extensive applications in domains such as sports training and medical rehabilitation.Nonetheless,existing research in the smart wearables domain predominantly emphasizes sensor functionality and quantity,often skipping crucial aspects related to user experience and interaction.Methods To address this gap,this study introduces a novel real-time 3D interactive system based on intelligent garments.The system utilizes lightweight sensor modules to collect human motion data and introduces a dual-stream fusion network based on pulsed neural units to classify and recognize human movements,thereby achieving real-time interaction between users and sensors.Additionally,the system incorporates 3D human visualization functionality,which visualizes sensor data and recognizes human actions as 3D models in real time,providing accurate and comprehensive visual feedback to help users better understand and analyze the details and features of human motion.This system has significant potential for applications in motion detection,medical monitoring,virtual reality,and other fields.The accurate classification of human actions contributes to the development of personalized training plans and injury prevention strategies.Conclusions This study has substantial implications in the domains of intelligent garments,human motion monitoring,and digital twin visualization.The advancement of this system is expected to propel the progress of wearable technology and foster a deeper comprehension of human motion.
基金supported by the Program of Entrepreneurship and Innovation Ph.D.in Jiangsu Province(JSSCBS20211175)the School Ph.D.Talent Funding(Z301B2055)the Natural Science Foundation of the Jiangsu Higher Education Institutions of China(21KJB520002).
文摘3D human pose estimation is a major focus area in the field of computer vision,which plays an important role in practical applications.This article summarizes the framework and research progress related to the estimation of monocular RGB images and videos.An overall perspective ofmethods integrated with deep learning is introduced.Novel image-based and video-based inputs are proposed as the analysis framework.From this viewpoint,common problems are discussed.The diversity of human postures usually leads to problems such as occlusion and ambiguity,and the lack of training datasets often results in poor generalization ability of the model.Regression methods are crucial for solving such problems.Considering image-based input,the multi-view method is commonly used to solve occlusion problems.Here,the multi-view method is analyzed comprehensively.By referring to video-based input,the human prior knowledge of restricted motion is used to predict human postures.In addition,structural constraints are widely used as prior knowledge.Furthermore,weakly supervised learningmethods are studied and discussed for these two types of inputs to improve the model generalization ability.The problem of insufficient training datasets must also be considered,especially because 3D datasets are usually biased and limited.Finally,emerging and popular datasets and evaluation indicators are discussed.The characteristics of the datasets and the relationships of the indicators are explained and highlighted.Thus,this article can be useful and instructive for researchers who are lacking in experience and find this field confusing.In addition,by providing an overview of 3D human pose estimation,this article sorts and refines recent studies on 3D human pose estimation.It describes kernel problems and common useful methods,and discusses the scope for further research.
文摘BACKGROUND： Many methods have been attempted to repair nerves following spinal cord injury, including peripheral nerve transplantation, Schwann cell transplantation, olfactory ensheathing cell transplantation, and embryonic neural tissue transplantation. However, there is a need for improved outcomes. OBJECTIVE： To investigate the repair feasibility for rat spinal cord injury using human neural stem cells （hNSCs） genetically modified by lentivirus to express neurotrophin-3. DESIGN, TIME AND SETTING： In vitro cell biological experiment and in vivo randomized, controlled genetic engineering experiment were performed at the Third Military Medical University of Chinese PLA and First People＇s Hospital of Yibin, China from March 2006 to December 2007. MATERIALS： A total of 64 adult, female, Wistar rats were used for the in vivo study. Of them, 48 rats were used to establish models of spinal cord hemisection, and were subsequently equally and randomly assigned to model, genetically modified hNSC, and normal hNSC groups. The remaining 16 rats served as normal controls. METHODS： hNSCs were in vitro genetically modified by lentivirus to secrete both green fluorescence protein and neurotrophin-3. Neurotrophin-3 expression was measured by Western blot. Genetically modified hNSC or normal hNSC suspension （5 × 10^5） was injected into the rat spinal cord following T10 spinal cord hemisection. A total of 5μL Dulbecco＇s-modified Eagle＇s medium was infused into the rat spinal cord in the model grop. Transgene expression and survival of transplanted hNSCs were determined by immunohistochemistry. Motor function was evaluated using the Basso, Beattie, and Bresnahan （BBB） scale. MAIN OUTCOME MEASURES： The following parameters were measured： expression of neurotrophin-3 produced by genetically modified hNSCs, transgene expression and survival of hNSCs in rats, motor function in rats. RESULTS： hNSCs were successfully genetically modified by lentivirus to stably express neurotrophin-3. The transplanted hNSCs primarily gathered at, or around, the injection site two weeks following transplantation, and gradually migrated towards the surrounding tissue. Transplanted hNSCs were observed 7.0-8.0 mm away from the injection site. In addition, hNSCs were observed 10 weeks after transplantation. At week 4, BBB locomotor scores were significantly greater in the genetically modified hNSC and normal hNSC groups, compared with the model group （P 〈 0.05）, and scores were significantly greater in the genetically modified hNSC group compared with the normal hNSC group （P 〈 0.05）. CONCLUSION： hNSCs were genetically modified with lentivirus to stably secrete neurotrophin-3. hNSCs improved motor function recovery in rats following spinal cord injury.
基金supported by the Key Project of NSFC(Grant No.U1908214)Special Project of Central Government Guiding Local Science and Technology Development(Grant No.2021JH6/10500140)+5 种基金the Program for Innovative Research Team in University of Liaoning Province(LT2020015)the Support Plan for Key Field Innovation Team of Dalian(2021RT06)the Support Plan for Leading Innovation Team of Dalian University(XLJ202010)the Science and Technology Innovation Fund of Dalian(Grant No.2020JJ25CY001)in part by the National Natural Science Foundation of China under Grant 61906032the FundamentalResearch Funds for the Central Universities under Grant DUT21TD107.
文摘With the advancement of image sensing technology, estimating 3Dhuman pose frommonocular video has becomea hot research topic in computer vision. 3D human pose estimation is an essential prerequisite for subsequentaction analysis and understanding. It empowers a wide spectrum of potential applications in various areas, suchas intelligent transportation, human-computer interaction, and medical rehabilitation. Currently, some methodsfor 3D human pose estimation in monocular video employ temporal convolutional network (TCN) to extractinter-frame feature relationships, but the majority of them suffer from insufficient inter-frame feature relationshipextractions. In this paper, we decompose the 3D joint location regression into the bone direction and length, wepropose the TCG, a temporal convolutional network incorporating Gaussian error linear units (GELU), to solvebone direction. It enablesmore inter-frame features to be captured andmakes the utmost of the feature relationshipsbetween data. Furthermore, we adopt kinematic structural information to solve bone length enhancing the use ofintra-frame joint features. Finally, we design a loss function for joint training of the bone direction estimationnetwork with the bone length estimation network. The proposed method has extensively experimented on thepublic benchmark dataset Human3.6M. Both quantitative and qualitative experimental results showed that theproposed method can achieve more accurate 3D human pose estimations.
基金Funding for this study from Sai Gon University(Grant No.CSA2021–08).
文摘3-dimension(3-D)printing technology is growing strongly with many applications,one of which is the garment industry.The application of human body models to the garment industry is necessary to respond to the increasing personalization demand and still guarantee aesthetics.This paper proposes amethod to construct 3-D human models by applying deep learning.We calculate the location of the main slices of the human body,including the neck,chest,belly,buttocks,and the rings of the extremities,using pre-existing information.Then,on the positioning frame,we find the key points(fixed and unaltered)of these key slices and update these points tomatch the current parameters.To add points to a star slice,we use a deep learning model tomimic the form of the human body at that slice position.We use interpolation to produce sub-slices of different body sections based on the main slices to create complete body parts morphologically.We combine all slices to construct a full 3-D representation of the human body.
文摘Purpose: Patient-specific quality assurance (PSQA) requires manual operation of different workstations, which is time-consuming and error-prone. Therefore, developing automated solutions to improve efficiency and accuracy is a priority. The purpose of this study was to develop a general software interface with scripting on a human interactive device (HID) for improving the efficiency and accuracy of manual quality assurance (QA) procedures. Methods: As an initial application, we aimed to automate our PSQA workflow that involves Varian Eclipse treatment planning system, Elekta MOSAIQ oncology information system and PTW Verisoft application. A general platform, the AutoFrame interface with two imbedded subsystems—the AutoFlow and the PyFlow, was developed with a scripting language for automating human operations of aforementioned systems. The interface included three functional modules: GUI module, UDF script interpreter and TCP/IP communication module. All workstations in the PSQA process were connected, and most manual operations were automated by AutoFrame sequentially or in parallel. Results: More than 20 PSQA tasks were performed both manually and using the developed AutoFrame interface. On average, 175 (±12) manual operations of the PSQA procedure were eliminated and performed by the automated process. The time to complete a PSQA task was 8.23 (±0.78) minutes for the automated workflow, in comparison to 13.91 (±3.01) minutes needed for manual operations. Conclusion: We have developed the AutoFrame interface framework that successfully automated our PSQA procedure, and significantly reduced the time, human (control/clicking/typing) errors, and operators’ stress. Future work will focus on improving the system’s flexibility and stability and extending its operations to other QA procedures.
基金supported by the National Natural Science Foundation of China, No. 30973262
文摘Neurotrophin-3 （NT-3） can promote the repair of central nervous system and retinal damage. In previous reports, NT-3 has been expressed by viral vectors. However, plasmid vectors have a safer profile compared with viral vectors in clinical studies. This study recombined amplified human retinal NT-3 with a eukaryotic expression plasmid containing green fluorescent protein （GFP） to construct an NT-3 expression plasmid, pEGFP-N1-NT-3. The transfection efficiency 48 hours after pEGFP-N1-NT-3 transfection to 293T cells was 50.06 ＋ 2.78%. Abundant NTo3-GFP was expressed in 293T cells as observed by fluorescence microscopy, suggesting the construct pEGFP-N1-NT-3 effectively expressed and secreted NT-3-GFP. Secretory vesicles containing NT-3-GFP were observed in a constant location in cells by laser scan confocal microscopy, indicating the expression and secretion processes of NT-3 in eukaryotic cells were in accordance with the physical synthesis processes of secreted proteins. Western blot assay showed that pro-NTo3-GFP had a molecular weight of 56 kDa, further confirming NT-3-GFP expression. At 48 hours after transfection, the concentration of NT-3 in culture medium was 22.3 ng/mL, suggesting NT-3 produced by pEGFP-N1-NT-3 was efficiently secreted. This study constructed a human retinal-derived NT-3 eukaryotic expression plasmid that efficiently expressed and secreted NT-3.
文摘BACKGROUND： Cell culture in vitro trials have demonstrated that neurotrophin-3 （NT-3） can enhance the survival of sensory neurons and sympathetic neurons, and can also support embryo-derived motor neurons. This effect is dependent on nerve growth factor on the surface of cells. Understanding the role of NT-3 and its receptor in the early development of human embryonic brains will help to investigate the correlation between early survival of nerve cells and the microenvironment of neural regeneration. OBJECTIVE： To observe the proliferation of cerebral neurons in the development of human embryonic brain, and to investigate the location, expression and distribution of NT-3 and its receptor TrkC during human brain development. DESIGN, TIME AND SETTING： An observation study on cells was performed in the Department of ttuman Anatomy, Histology and Embryology, Chengdu Medical College in September 2007. MATERIALS： Fifteen specimens of flesh human embryo, aged 6 weeks, were used in this study. METHODS： The proliferation of cerebral neurons was detected using proliferating cell nuclear antigen, and the immunocytochemistry ABC technique was applied to observe the location, expression and distribution of NT-3 and its receptor TrkC in the brain of the human embryo. MAIN OUTCOME MEASURES： Location, expression and distribution of NT-3 and its receptor in the brain of the human embryo. RESULTS： In the early period （aged 6 weeks） of human embryonic development, proliferating cell nuclear antigen-positive reactive substances were mainly observed in the nucleus of the forebrain ventricular zone and subventricular zone, and the intensity was stronger in the subventricular zone than the forebrain ventricle. NT-3 positive reactive substance was mainly distributed in the cytoblastema of the forebrain neuroepithelial layer and nerve cell process, while TrkC was mainly distributed in the cell membrane of the forebrain ventricular zone and subventricular zone. During embryonic development, NT-3 and TrkC showed a positive immune reaction to a greater or lesser extent in ependymal epithelium. CONCLUSION： During early human embryonic development, cerebral nerve cells proliferate in the ventricular zone and subventricular zone, and NT-3 is expressed in the neural axon. The results show that the highly expressed NT-3 could promote the proliferation of neural axons and maintain the neuron body＇s survival.
