Severe acute respiratory syndrome coronavirus 2(SARS-CoV-2)mutations are influenced by random and uncontrollable factors,and the risk of the next widespread epidemic remains.Dual-target drugs that synergistically act ...Severe acute respiratory syndrome coronavirus 2(SARS-CoV-2)mutations are influenced by random and uncontrollable factors,and the risk of the next widespread epidemic remains.Dual-target drugs that synergistically act on two targets exhibit strong therapeutic effects and advantages against mutations.In this study,a novel computational workflow was developed to design dual-target SARS-CoV-2 candidate inhibitors with the Envelope protein and Main protease selected as the two target proteins.The drug-like molecules of our self-constructed 3D scaffold database were used as high-throughput molecular docking probes for feature extraction of two target protein pockets.A multi-layer perceptron(MLP)was employed to embed the binding affinities into a latent space as conditional vectors to control conditional distribution.Utilizing a conditional generative neural network,cG-SchNet,with 3D Euclidean group(E3)symmetries,the conditional probability distributions of molecular 3D structures were acquired and a set of novel SARS-CoV-2 dual-target candidate inhibitors were generated.The 1D probability,2D joint probability,and 2D cumulative probability distribution results indicate that the generated sets are significantly enhanced compared to the training set in the high binding affinity area.Among the 201 generated molecules,42 molecules exhibited a sum binding affinity exceeding 17.0 kcal/mol while 9 of them having a sum binding affinity exceeding 19.0 kcal/mol,demonstrating structure diversity along with strong dual-target affinities,good absorption,distribution,metabolism,excretion,and toxicity(ADMET)properties,and ease of synthesis.Dual-target drugs are rare and difficult to find,and our“high-throughput docking-multi-conditional generation”workflow offers a wide range of options for designing or optimizing potent dual-target SARS-CoV-2 inhibitors.展开更多
Equatorial Plasma Bubbles(EPBs)are ionospheric irregularities that take place near the magnetic equator.EPBs most commonly occur after sunset during the equinox months,although they can also be observed during other s...Equatorial Plasma Bubbles(EPBs)are ionospheric irregularities that take place near the magnetic equator.EPBs most commonly occur after sunset during the equinox months,although they can also be observed during other seasons.The phenomenon significantly disrupts radio wave signals essential to communication and navigation systems.The national network of Global Navigation Satellite System(GNSS)receivers in Indonesia(>30°longitudinal range)provides an opportunity for detailed EPB studies.To explore this,we conducted preliminary 3D tomography of total electron content(TEC)data captured by GNSS receivers following a geomagnetic storm on December 3,2023,when at least four EPB clusters occurred in the Southeast Asian sector.TEC and extracted TEC depletion with a 120-minute running average were then used as inputs for a 3D tomography program.Their 2D spatial distribution consistently captured the four EPB clusters over time.These tomography results were validated through a classical checkerboard test and comparisons with other ionospheric data sources,such as the Global Ionospheric Map(GIM)and International Reference Ionosphere(IRI)profile.Validation of the results demonstrates the capability of the Indonesian GNSS network to measure peak ionospheric density.These findings highlight the potential for future three-dimensional research of plasma bubbles in low-latitude regions using existing GNSS networks,with extensive longitudinal coverage.展开更多
As an essential field of multimedia and computer vision,3D shape recognition has attracted much research attention in recent years.Multiview-based approaches have demonstrated their superiority in generating effective...As an essential field of multimedia and computer vision,3D shape recognition has attracted much research attention in recent years.Multiview-based approaches have demonstrated their superiority in generating effective 3D shape representations.Typical methods usually extract the multiview global features and aggregate them together to generate 3D shape descriptors.However,there exist two disadvantages:First,the mainstream methods ignore the comprehensive exploration of local information in each view.Second,many approaches roughly aggregate multiview features by adding or concatenating them together.The information loss for some discriminative characteristics limits the representation effectiveness.To address these problems,a novel architecture named region-based joint attention network(RJAN)was proposed.Specifically,the authors first design a hierarchical local information exploration module for view descriptor extraction.The region-to-region and channel-to-channel relationships from different granularities can be comprehensively explored and utilised to provide more discriminative characteristics for view feature learning.Subsequently,a novel relation-aware view aggregation module is designed to aggregate the multiview features for shape descriptor generation,considering the view-to-view relationships.Extensive experiments were conducted on three public databases:ModelNet40,ModelNet10,and ShapeNetCore55.RJAN achieves state-of-the-art performance in the tasks of 3D shape classification and 3D shape retrieval,which demonstrates the effectiveness of RJAN.The code has been released on https://github.com/slurrpp/RJAN.展开更多
目的:近年来,许多学者将3D打印人工椎体应用于颈椎前路椎体次全切除植骨融合术中,但是与传统钛笼相比是否疗效更佳尚存争议。为此,拟系统评价3D打印人工椎体对比传统钛笼作为内植物应用于颈椎前路椎体次全切除植骨融合治疗颈椎病的有效...目的:近年来,许多学者将3D打印人工椎体应用于颈椎前路椎体次全切除植骨融合术中,但是与传统钛笼相比是否疗效更佳尚存争议。为此,拟系统评价3D打印人工椎体对比传统钛笼作为内植物应用于颈椎前路椎体次全切除植骨融合治疗颈椎病的有效性与安全性。方法:计算机检索CNKI、WangFang、CBM、VIP、PubMed、EMBASE、The Cochrane Library数据库,搜集各数据库建库至2025年2月有关3D打印人工椎体应用于颈椎前路椎体次全切除植骨融合的临床研究。筛选文献、提取资料并评价纳入研究的方法学质量后,采用Rev Man 5.4软件进行Meta分析。结果:①共纳入10篇文献,包含2篇前瞻性随机对照研究,6篇回顾性队列研究,2篇前瞻性队列研究,均为高质量研究;所纳入的文献共包含534例患者,其中3D打印组273例,对照组261例;②Meta分析结果显示:3D打印组在手术时间[SMD=-1.13,95%CI(-1.87,-0.39),P=0.003]、术后末次随访椎间隙丢失高度[SMD=-3.01,95%CI(-5.74,-0.29),P=0.03]、术后3个月颈椎功能障碍指数[SMD=-0.34,95%CI(-0.66,-0.03),P=0.03]、假体塌陷率[OR=0.19,95%CI(0.11,0.32),P<0.00001]、术后吞咽不适发生率[OR=0.43,95%CI(0.21,0.90),P=0.03]方面均优于对照组,差异有显著性意义;在手术出血量、住院时间、术后日本骨科协会评分、术后目测类比评分、术后颈椎功能障碍指数(术后6个月、末次随访)、椎体融合率方面,两组差异无显著性意义(P>0.05)。结论:与传统钛笼相比,3D打印人工椎体在提高手术效率、维持术后椎间隙高度、减少术后吞咽不适发生率及假体塌陷率方面具有明显优势。展开更多
基金supported by Interdisciplinary Innova-tion Project of“Bioarchaeology Laboratory”of Jilin University,China,and“MedicineþX”Interdisciplinary Innovation Team of Norman Bethune Health Science Center of Jilin University,China(Grant No.:2022JBGS05).
文摘Severe acute respiratory syndrome coronavirus 2(SARS-CoV-2)mutations are influenced by random and uncontrollable factors,and the risk of the next widespread epidemic remains.Dual-target drugs that synergistically act on two targets exhibit strong therapeutic effects and advantages against mutations.In this study,a novel computational workflow was developed to design dual-target SARS-CoV-2 candidate inhibitors with the Envelope protein and Main protease selected as the two target proteins.The drug-like molecules of our self-constructed 3D scaffold database were used as high-throughput molecular docking probes for feature extraction of two target protein pockets.A multi-layer perceptron(MLP)was employed to embed the binding affinities into a latent space as conditional vectors to control conditional distribution.Utilizing a conditional generative neural network,cG-SchNet,with 3D Euclidean group(E3)symmetries,the conditional probability distributions of molecular 3D structures were acquired and a set of novel SARS-CoV-2 dual-target candidate inhibitors were generated.The 1D probability,2D joint probability,and 2D cumulative probability distribution results indicate that the generated sets are significantly enhanced compared to the training set in the high binding affinity area.Among the 201 generated molecules,42 molecules exhibited a sum binding affinity exceeding 17.0 kcal/mol while 9 of them having a sum binding affinity exceeding 19.0 kcal/mol,demonstrating structure diversity along with strong dual-target affinities,good absorption,distribution,metabolism,excretion,and toxicity(ADMET)properties,and ease of synthesis.Dual-target drugs are rare and difficult to find,and our“high-throughput docking-multi-conditional generation”workflow offers a wide range of options for designing or optimizing potent dual-target SARS-CoV-2 inhibitors.
基金the National Institute of Information and Communication Technology International Exchange Program 2024−2025(No.2024−007)for their invaluable support in this research.3D tomography software is available at Prof.Kosuke Heki’s(Hokkaido University,Japan)personal homepage(https://www.ep.sci.hokudai.ac.jp/~heki/software.htm).support from the 2024 Japan Student Services Organization Research Follow-up Fellowship for a 90-day research visit at the Institute for Space−Earth Environmental Research,Nagoya University,Japan.PA also acknowledges the support received from Telkom University under the“Skema Penelitian Terapan Periode I Tahun Anggaran 2024”,and the Memorandum of Understanding for Research Collaboration on Regional Ionospheric Observation(No:092/SAM3/TE-DEK/2021).
文摘Equatorial Plasma Bubbles(EPBs)are ionospheric irregularities that take place near the magnetic equator.EPBs most commonly occur after sunset during the equinox months,although they can also be observed during other seasons.The phenomenon significantly disrupts radio wave signals essential to communication and navigation systems.The national network of Global Navigation Satellite System(GNSS)receivers in Indonesia(>30°longitudinal range)provides an opportunity for detailed EPB studies.To explore this,we conducted preliminary 3D tomography of total electron content(TEC)data captured by GNSS receivers following a geomagnetic storm on December 3,2023,when at least four EPB clusters occurred in the Southeast Asian sector.TEC and extracted TEC depletion with a 120-minute running average were then used as inputs for a 3D tomography program.Their 2D spatial distribution consistently captured the four EPB clusters over time.These tomography results were validated through a classical checkerboard test and comparisons with other ionospheric data sources,such as the Global Ionospheric Map(GIM)and International Reference Ionosphere(IRI)profile.Validation of the results demonstrates the capability of the Indonesian GNSS network to measure peak ionospheric density.These findings highlight the potential for future three-dimensional research of plasma bubbles in low-latitude regions using existing GNSS networks,with extensive longitudinal coverage.
基金the National Key Research and Development Program of China,Grant/Award Number:2020YFB1711704the National Natural Science Foundation of China,Grant/Award Number:62272337。
文摘As an essential field of multimedia and computer vision,3D shape recognition has attracted much research attention in recent years.Multiview-based approaches have demonstrated their superiority in generating effective 3D shape representations.Typical methods usually extract the multiview global features and aggregate them together to generate 3D shape descriptors.However,there exist two disadvantages:First,the mainstream methods ignore the comprehensive exploration of local information in each view.Second,many approaches roughly aggregate multiview features by adding or concatenating them together.The information loss for some discriminative characteristics limits the representation effectiveness.To address these problems,a novel architecture named region-based joint attention network(RJAN)was proposed.Specifically,the authors first design a hierarchical local information exploration module for view descriptor extraction.The region-to-region and channel-to-channel relationships from different granularities can be comprehensively explored and utilised to provide more discriminative characteristics for view feature learning.Subsequently,a novel relation-aware view aggregation module is designed to aggregate the multiview features for shape descriptor generation,considering the view-to-view relationships.Extensive experiments were conducted on three public databases:ModelNet40,ModelNet10,and ShapeNetCore55.RJAN achieves state-of-the-art performance in the tasks of 3D shape classification and 3D shape retrieval,which demonstrates the effectiveness of RJAN.The code has been released on https://github.com/slurrpp/RJAN.
文摘目的:近年来,许多学者将3D打印人工椎体应用于颈椎前路椎体次全切除植骨融合术中,但是与传统钛笼相比是否疗效更佳尚存争议。为此,拟系统评价3D打印人工椎体对比传统钛笼作为内植物应用于颈椎前路椎体次全切除植骨融合治疗颈椎病的有效性与安全性。方法:计算机检索CNKI、WangFang、CBM、VIP、PubMed、EMBASE、The Cochrane Library数据库,搜集各数据库建库至2025年2月有关3D打印人工椎体应用于颈椎前路椎体次全切除植骨融合的临床研究。筛选文献、提取资料并评价纳入研究的方法学质量后,采用Rev Man 5.4软件进行Meta分析。结果:①共纳入10篇文献,包含2篇前瞻性随机对照研究,6篇回顾性队列研究,2篇前瞻性队列研究,均为高质量研究;所纳入的文献共包含534例患者,其中3D打印组273例,对照组261例;②Meta分析结果显示:3D打印组在手术时间[SMD=-1.13,95%CI(-1.87,-0.39),P=0.003]、术后末次随访椎间隙丢失高度[SMD=-3.01,95%CI(-5.74,-0.29),P=0.03]、术后3个月颈椎功能障碍指数[SMD=-0.34,95%CI(-0.66,-0.03),P=0.03]、假体塌陷率[OR=0.19,95%CI(0.11,0.32),P<0.00001]、术后吞咽不适发生率[OR=0.43,95%CI(0.21,0.90),P=0.03]方面均优于对照组,差异有显著性意义;在手术出血量、住院时间、术后日本骨科协会评分、术后目测类比评分、术后颈椎功能障碍指数(术后6个月、末次随访)、椎体融合率方面,两组差异无显著性意义(P>0.05)。结论:与传统钛笼相比,3D打印人工椎体在提高手术效率、维持术后椎间隙高度、减少术后吞咽不适发生率及假体塌陷率方面具有明显优势。
