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Screening biomarkers for spinal cord injury using weighted gene co-expression network analysis and machine learning

Neural Regeneration research 2024年第12期19卷 2723-2734页

作者： Xiaolu Li Ye Yang Senming Xu Yuchang Gui Jianmin Chen Jianwen Xu Department of Rehabilitation Medicine The First Affiliated Hospital of Guangxi Medical UniversityNanningGuangxi Zhuang Autonomous RegionChina Department of Rehabilitation Medicine Guilin People’s HospitalGuilinGuangxi Zhuang Autonomous RegionChina Department of Rehabilitation Medicine The First Affiliated Hospital of Fujian Medical UniversityFuzhouFujian ProvinceChina

Immune changes and inflammatory responses have been identified as central events in the pathological process of spinal co rd *** can greatly affect nerve regeneration and functional ***,there is still limited understanding of the peripheral immune inflammato ry response in spinal cord inju *** this *** obtained microRNA expression profiles from the peripheral blood of patients with spinal co rd injury using high-throughput *** also obtained the mRNA expression profile of spinal cord injury patients from the Gene Expression Omnibus(GEO)database(GSE151371).We identified 54 differentially expressed microRNAs and 1656 diffe rentially expressed genes using bioinformatics *** enrichment analysis revealed that various common immune and inflammation-related signaling pathways,such as neutrophil extracellular trap formation pathway,T cell receptor signaling pathway,and nuclear factor-κB signal pathway,we re abnormally activated or inhibited in spinal cord inju ry patient *** applied an integrated strategy that combines weighted gene co-expression network analysis,LASSO logistic regression,and SVM-RFE algorithm and identified three biomarke rs associated with spinal cord injury:ANO10,BST1,and *** verified the expression levels and diagnostic perfo rmance of these three genes in the original training dataset and clinical samples through the receiver operating characteristic *** polymerase chain reaction results showed that ANO20 and BST1 mRNA levels were increased and ZFP36L2 mRNA was decreased in the peripheral blood of spinal cord injury *** also constructed a small RNA-mRNA interaction network using ***,we evaluated the proportion of 22 types of immune cells in the peripheral blood of spinal co rd injury patients using the CIBERSORT *** proportions of naive B cells,plasma cells,monocytes,and neutrophils were increased while the proportions of memory B cells,C

关键词： bioinformatics analysis biomarker CIBERSORT GEO dataset LASSO miRNA-mRNA network RNA sequencing spinal cord injury SVM-RFE weighted gene co-expression network analysis

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Learning Scalable Task Assignment with Imperative-Priori Conflict Resolution in Multi-UAV Adversarial Swarm Defense Problem

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Journal of systems Science & Complexity 2024年第1期37卷 369-388页

作者： ZHAO Zhixin CHEN Jie XIN Bin LI Li JIAO Keming ZHENG Yifan School of Electronics and Information Engineering Tongji UniversityShanghai 201804China Shanghai Institute of Intelligent Science and Technology Tongji UniversityShanghai 201804China School of Automation Beijing Institute of TechnologyBeijing 100081China National Key Laboratory of autonomous Intelligent Unmanned systems Beijing 100081China Shanghai Institute of Intelligent Science and Technology Tongji UniversityShanghai 201804China.

The multi-UAV adversary swarm defense(MUASD)problem is to defend a static base against an adversary UAV swarm by a defensive UAV *** the problem into task assignment and low-level interception strategies is a widely used ***-based approaches for task assignment are a promising *** studies on learning-based methods generally assume decentralized decision-making architecture,which is not beneficial for conflict *** contrast,centralized decision-making architecture is beneficial for conflict resolution while it is often detrimental to *** achieve scalability and conflict resolution simultaneously,inspired by a self-attention-based task assignment method for sensor target coverage problem,a scalable centralized assignment method based on self-attention mechanism together with a defender-attacker pairwise observation preprocessing(DAP-SelfAtt)is ***,an imperative-priori conflict resolution(IPCR)mechanism is proposed to achieve conflict-free ***,the IPCR mechanism is parallelized to enable efficient *** validate the algorithm,a variant of proximal policy optimization algorithm(PPO)is employed for training in scenarios of various *** experimental results show that the proposed algorithm not only achieves conflict-free task assignment but also maintains scalability,and significantly improve the success rate of defense.

关键词： Conflict resolution reinforcement learning scalability task assignment.

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DGConv: A Novel Convolutional Neural Network Approach for Weld Seam Depth Image Detection

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Computers, Materials & Continua 2024年第2期78卷 1755-1771页

作者： Pengchao Li Fang Xu Jintao Wang Haibing Guo Mingmin Liu Zhenjun Du State Key Laboratory of robotics Shenyang Institute of AutomationChinese Academy of SciencesShenyang110016China Institutes for robotics and Intelligent Manufacturing Chinese Academy of SciencesShenyang110169China University of Chinese Academy of Sciences Beijing100049China Shenyang SIASUN Robot&Automation Co. Ltd.Shenyang110168China

We propose a novel image segmentation algorithm to tackle the challenge of limited recognition and segmentation performance in identifying welding seam images during robotic intelligent ***,to enhance the capability of deep neural networks in extracting geometric attributes from depth images,we developed a novel deep geometric convolution operator(DGConv).DGConv is utilized to construct a deep local geometric feature extraction module,facilitating a more comprehensive exploration of the intrinsic geometric information within depth ***,we integrate the newly proposed deep geometric feature module with the Fully Convolutional Network(FCN8)to establish a high-performance deep neural network algorithm tailored for depth image ***,we enhance the FCN8 detection head by separating the segmentation and classification *** enhancement significantly boosts the network’s overall detection ***,for a comprehensive assessment of our proposed algorithm and its applicability in real-world industrial settings,we curated a line-scan image dataset featuring weld *** dataset,named the Standardized Linear Depth Profile(SLDP)dataset,was collected from actual industrial sites where autonomous robots are in ***,we conducted experiments utilizing the SLDP dataset,achieving an average accuracy of 92.7%.Our proposed approach exhibited a remarkable performance improvement over the prior method on the identical ***,we have successfully deployed the proposed algorithm in genuine industrial environments,fulfilling the prerequisites of unmanned robot operations.

关键词： Weld image detection deep learning semantic segmentation depth map geometric feature extraction

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Impact of data balancing a multiclass dataset before the creation of association rules to study bacterial vaginosis

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Intelligent Medicine 2024年第3期4卷 188-199页

作者： Freddy de la Cruz-Ruiz Juana Canul-Reich Rafael Rivera-López Erick de la Cruz-Hernández Academic Division of Science and Technology of the Information Juárez Autonomous University of TabascoLa Esmeralda DistrictTabascoMexico Department of systems National Technological Institute of MexicoTechnological Institute of VeracruzVeracruzMexico Multidisciplinary Academic Division of Comalcalco Juárez Autonomous University of TabascoTabascoMexico

Background Bacterial vaginosis is a polymicrobial syndrome in which the homeostasis exerted by the Latobacillus species that protect the vaginal mucosa has been *** study explored the data balancing process with the intention of improving the quality of association *** article aimed to balance the unbalanced multiclass dataset to improve association rule *** A dataset with 201 observations and 58 variables was analyzed.A preconstructed dataset was *** authors collected the data between August 2016 and October 2018 in Tabasco,*** study population comprised sexually active women ages 18 to 50 who underwent gynecological inspection at the infectious and metabolic diseases research laboratory at the Universidad Juarez Autonoma de *** determine the best κ-value,the random-forest algorithm was used and the balancing was performed with the synthetic minority over-sampling technique(SMOTE),random over-sampling examples(ROSE),and adaptive syntetic sampling approach for imbalanced learning(ADASYN)*** Apriori algorithm created the rules and to select rules with statistical significance,the ***(),***(),and ***()functions and quality metric Fisher’s exact tes were *** biological validation was carried out by the expert(bacteriologist).Results The ADASYN algorithm at K=9 the out of the bag(OOB)error was zero,this was the best𝐾-*** the balancing process the ADASYN algorithm show best the *** the dataset balanced with ADASYN,the apriori algorithm created the association rules and the selection with the quality metric Fisher’s exact test,and the biological validation reported 13 ***-bacteria Atopobium vaginae,Gardnerella vaginalis,Megasphaera filotipo 1,Mycoplasma hominis and Ureaplasma parvum were detected by the apriori algorithm from the balanced *** Balancing may improve the creation of association rules to efficiently model the bacteria that cause bac

关键词： Bacterial vaginosis Data balancing Random forest Synthetic minority over-sampling technique

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Time-Series Embeddings from Language Models:A Tool for Wind Direction Nowcasting

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Journal of Meteorological research 2024年第3期38卷 558-569页

作者： Decio ALVES Fabio MENDONCA Sheikh Shanawaz MOSTAFA Fernando MORGADO-DIAS University of Madeira Campus Universitário da Penteada9020-105FunchalPortugal Interactive Technologies Institute/Laboratory for robotics and Engineering systems and Agência Regional para o Desenvolvimento da Investigação Tecnologia e InovaçãoEdif.Madeira TecnopoloCaminho da Penteada piso-29020-105FunchalPortugal

Wind direction nowcasting is crucial in various sectors,particularly for ensuring aviation operations and *** this context,the TELMo(Time-series Embeddings from Language Models)model,a sophisticated deep learning architecture,has been introduced in this work for enhanced wind-direction *** by using three years of data from multiple stations in the complex terrain of an international airport,TELMo incorporates the horizontal u(east-west)and v(north-south)wind components to significantly reduce forecasting *** a day with high wind direction variability,TELMo achieved mean absolute error values of 5.66 for 2-min,10.59 for 10-min,and 14.79 for 20-min forecasts,processed within a swift 9-ms/step *** degree-based analysis,in comparison,yielded lower performance,emphasizing the effectiveness of the u and v *** contrast,a Vanilla neural network,representing a shallow-learning approach,underperformed in all analyses,highlighting the superiority of deep learning methodologies in wind direction *** is an efficient model,capable of accurately forecasting wind direction for air traffic operations,with an error less than 20°in 97.49%of the predictions,aligning with recommended international *** model design enables its applicability across various geographical locations,making it a versatile tool in global aviation meteorology.

关键词： wind nowcasting wind components wind direction time series prediction deep learning

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Analysis of Epidemiological and Issues Encountered in Case Reports on Echinococcosis—China,2022

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China CDC weekly 2024年第6期6卷 100-104页

作者： Yan Kui Shuai Han Xiaojuan Zhang Guangzhong Shi Yale Yu Ruirui Li Peizheng Zhan Hongju Duan Wenbo Luo Benfu Li Shaoqi Ning Yalan Zhang Aiya Zhu Jingbo Xue National Institute of Parasitic Diseases Chinese Center for Disease Control and Prevention(Chinese Center for Tropical Diseases Research)National Health Commission Key Laboratory of Parasite and Vector BiologyWorld Health Organization Collaborating Center for Tropical DiseasesNational Center for International Research on Tropical DiseasesShanghaiChina Gansu Provincial Center for Disease Control and Prevention Lanzhou CityGansu ProvinceChina The Center for Disease Control and Prevention of Xinjiang Uygur autonomous Region Urumuqi CityXinjiang Uygur Autonomous RegionChina Xinjiang Production and Construction Corps Center for Disease Control and Prevention Urumuqi CityXinjiang Uygur Autonomous RegionChina Sichuan Provincial Center for Disease Control and Prevention Chengdu CitySichuan ProvinceChina Qinhai Institute for Endemic Disease Control and Prevention Xining CityQinghai ProvinceChina Ningxia Center for Disease Control and Prevention Yinchuan CityNingxia Hui Autonomous RegionChina Inner Mongolia autonomous Region Center for Comprehensive Disease Control and Prevention Hohhot CityInner Mongolia AutonomousChina Yunnan Institute of Parasitic Diseases Puer CityYunnan ProvinceChina Shaanxi Provincial Center for Disease Control and Prevention Xi'an CityShaanxi ProvinceChina Henan Provincial Center for Disease Control and Prevention Zhengzhou CityHenan ProvinceChina Guizhou Provincial Center for Disease Control and Prevention Guiyang CityGuizhou ProvinceChina

Summary What is already known about this topic?Echinococcosis is classified as a Class C infectious disease in *** is endemic in 370 counties located in the agricultural and pastoral regions of western *** is added by this report?This report provides a comprehensive overview of the cases of echinococcosis reported in China in *** a thorough evaluation conducted by provincial CDCs.

关键词： China Ech counties

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Structural,morphological,optical and antibacterial performances of rare earth(Sm)-doped ZnO nanorods

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Journal of Rare Earths 2024年第11期42卷 2119-2127页

作者： A.Ravi J.Samuel S.Sahaya Jude Dhas S.Usharani Turibius Simon D.Senthil Kumar S.K.Jasmin Vijitha A.Sivakumar Raju Suresh Kumar C.S.Biju Department of Physics University College of Engineering Department of Physics and research centre Malankara Catholic College Manonmaniam Sundaranar University Saveetha School of Engineering Saveetha Institute of Medical and Technical SciencesSaveetha University Department of Chemistry S.I.V.E.T College Department of Biotechnology Vivekanandha College of Arts and Science for Woman (Autonomous) Department of Physics Vel Tech Rangarajan Dr.Sagunthala R & D Institute of Science and Technology Department of Physics & research centre Muslim Arts College Key Laboratory of High-temperature and High-pressure Study of the Earth's Interior Institute of GeochemistryChinese Academy of Sciences Department of Chemistry College of ScienceKing Saud University Department of Physics St. Alphonsa College of Arts and Science

The significant rise of ultra-violet（UV） radiation and pathogenic infectious bacteria poses a serious threat to global *** researchers' interests are attracted by novel materials with strong UVblocking ability,antibacterial activity and low toxicity to other *** this case,a simple wet chemical method with different annealing temperatures（400,500,and 600℃） was employed to create highly effective rare earth（Sm）-doped ZnO ***（101） plane of wurtzite ZnO shifts towards a lower angle with increasing annealing temperature,according to the X-ray diffraction（XRD） study findings,which additionally establishes the consequence of lattice *** of doublet peaks of Sm 3d(Sm 3d5/2and Sm 3d3/2) in the X-ray photoelectron spectroscopy（XPS） spectrum clearly validates the substitution of Sm3+ions in the 500℃-annealed *** 500℃-annealed nanorods exhibit combined performances of the wide band gap,improved UV absorbance,and vivid green luminescent emission（563 nm）.Additio nally,the nanorods have favorable UV-blocking execution of 96% for UVA at 360 nm,92% for UVB at 320 nm,and 57% for UVC at 225 nm,which is greater than the majority of ZnO-related materials that have been reported up to this *** doping is also appropriate for improving bacterial inhibition against the two studied strains（Escherichia coli and Staphylococcus aureus）,in addition to the intriguing features discussed ***,with maximum inhibition zone diameters of 20±0.72 and 18±0.57 mm,respectively,these nanorods exhibit high inhibitory action against *** and *** bacterial *** rare earth-doped material developed during the current experiment,which was annealed at 500℃,could potentially serve as an effective replacement for UV-blocking and antibacterial material,especially for biomedical applications.

关键词： Bacterial inhibition Metal oxide Rare earth doping UV-Shielding Wet chemical method

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Hypolipidemic activity and mechanism of active components of Dracocephalum moldavica L. tea

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Food Science and Human Wellness 2024年

作者： Siqi Li Qinyu Li Na Zhang Minhui Li Inner Mongolia autonomous Region Hospital of Traditional Chinese Medicine Inner Mongolia Traditional Chinese and Mongolian Medical research Institute Department of Pharmacy， Baotou Medical College

Hyperlipidemia is associated with many diseases and considered the main contributing factor in the development of metabolic syndrome. The traditional Mongolian medicine Dracocephalum moldavica L. (D. moldavica) is commonly consumed as a tea (non-Camellia tea) for the prevention and treatment of coronary heart disease， hypertension， atherosclerosis， and other diseases. Here， we attempted to investigate the hypolipidemic activity and mechanisms underlying the active components of D. moldavica. First， the mechanism underlying the lipid accumulation-reducing effects of the D. moldavica ethanol extract was determined using in vitro experiments， and four polar fractions were screened for activity. Then， the effect of the ethyl acetate fraction of D. moldavica (EAD) on lowering blood lipid was confirmed in vivo. The combination of network pharmacological and serum pharmacochemistry analyses showed that apigenin， luteolin， and naringenin of EAD existed in prototype form in the drug-containing serum of rats. We also determined the content of the three active ingredients in EAD. Finally， in vitro experiments showed that apigenin， luteolin， and naringenin improved oleic acid-induced lipid accumulation in HepG2 cells by regulating the PPAR signaling pathway (PPARα， CPT1， and FABP3). Our findings provide mechanistic insights and application prospects for the prevention and treatment of hypolipidemia using D. moldavica.

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Towards robustness and generalization of point cloud representation:A geometry coding method and a large-scale object-level dataset

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Computational Visual Media 2024年第1期10卷 27-43页

作者： Mingye Xu Zhipeng Zhou Yali Wang Yu Qiao Guangdong-Hong Kong-Macao Joint Laboratory of Human-Machine Intelligence-Synergy systems Shenzhen Institute of Advanced TechnologyChinese Academy of SciencesShenzhen518000China University of Chinese Academy of Sciences Beijing065001China Shanghai AI Laboratory Shanghai200001China SIAT Branch Shenzhen Institute of Artificial Intelligence and Robotics for SocietyShenzhen518000China Alibaba DAMO Academy Hangzhou242332China

Robustness and generalization are two challenging problems for learning point cloud *** tackle these problems,we first design a novel geometry coding model,which can effectively use an invariant eigengraph to group points with similar geometric information,even when such points are far from each *** also introduce a large-scale point cloud dataset,*** consists of 184 categories and 51,915 synthetic objects,which brings new challenges for point cloud classification,and provides a new benchmark to assess point cloud cross-domain ***,we perform extensive experiments on point cloud classification,using ModelNet40,ScanObjectNN,and our PCNet184,and segmentation,using ShapeNetPart and *** method achieves comparable performance to state-of-the-art methods on these datasets,for both supervised and unsupervised *** and our dataset are available at https://***/MingyeXu/PCNet184.

关键词： geometry coding self-supervised learning point cloud classification segmentation 3D analysis

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Heavy metal pollution of river water and eco-friendly remediation using potent microalgal species

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Water Science and Engineering 2024年第1期17卷 41-50页

作者： Amudham Radha Amal Raj Prabhakaran Mylsamy V.Sivasankar B.Sathish Kumar Kiyoshi Omine T.G.Sunitha Phycological research Laboratory Research Department of BotanyPachaiyappa's College(Affiliated to University of Madras)Chennai 600030India research Department of Chemistry Pachaiyappa's College(Affiliated to University of Madras)Chennai 600030India Department of Botany Sri Vidya Mandir Arts&Science College(Autonomous)KatteriUthangarai 636902India Department of Civil Engineering School of Engineering.Nagasaki UniversityNagasaki-Daigaku1-14 Bunkyo-machiNagasaki 8528521Japan

Pollution of rivers is mainly caused by anthropogenic activities such as discharge of effluent from industrial facilities,maintenance of sewage/effluent treatment plants,and dumping of solid waste on river *** study dealt with the pollution issues of the Cooum River in the well-known city of Chennai in South *** samples from 27 locations were collected and analyzed for 12 elements,including Ba,B,and Al,as well as heavy metals such as Pb,Cr,Mn,Fe,Co,Ni,Cu,Zn,and *** samples showed levels of these elements that exceeded World Health Organization *** correlation analysis revealed the inter-dependency among elements,and the contribution of each element based on factor loadings showed its percentage contribution compared to *** samples from six significant locations were chosen for remediation with three algae:Chlorella vulgaris,Scenedesmus dimorphus,and Phormedium *** uptake of pollutants led to the continuous growth of algae during the incubation period of 15 d,effectively removing heavy metals from the river *** increasing levels of algal counts and the chlorophyll a content confirmed the algal growth during the incubation period,followed by a declining stage after the incubation *** scanning electron microscopic images of algae before and after the remediation showed no remarkable modification of morphological *** study showed that the uptake of heavy metals using algae is an effective water pollution remediation measure,making the process practicable in the field on a large scale in the near future.

关键词： Heavy metal Cooum river Phycoremediation Microalgae Factor analysis

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