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Automatic detection of small bowel lesions with different bleeding risks based on deep learning models

World Journal of Gastroenterology 2024年第2期30卷 170-183页

作者： Rui-Ya zhang Peng-Peng Qiang Ling-Jun Cai Tao Li Yan Qin Yu zhang Yi-Qing Zhao Jun-Ping Wang Department of Gastroenterology The Fifth Clinical Medical College of Shanxi Medical UniversityTaiyuan 030012Shanxi ProvinceChina School of Computer and Information Technology Shanxi UniversityTaiyuan 030006Shanxi ProvinceChina School of Life Sciences and Technology Mudanjiang Normal UniversityMudanjiang 157011Heilongjiang ProvinceChina

BACKGROUND Deep learning provides an efficient automatic image recognition method for small bowel(SB)capsule endoscopy(CE)that can assist physicians in ***,the existing deep learning models present some unresolved *** To propose a novel and effective classification and detection model to automatically identify various SB lesions and their bleeding risks,and label the lesions accurately so as to enhance the diagnostic efficiency of physicians and the ability to identify high-risk bleeding *** The proposed model represents a two-stage method that combined image classification with object ***,we utilized the improved ResNet-50 classification model to classify endoscopic images into SB lesion images,normal SB mucosa images,and invalid ***,the improved YOLO-V5 detection model was utilized to detect the type of lesion and its risk of bleeding,and the location of the lesion was *** constructed training and testing sets and compared model-assisted reading with physician *** The accuracy of the model constructed in this study reached 98.96%,which was higher than the accuracy of other systems using only a single *** sensitivity,specificity,and accuracy of the model-assisted reading detection of all images were 99.17%,99.92%,and 99.86%,which were significantly higher than those of the endoscopists’*** image processing time of the model was 48 ms/image,and the image processing time of the physicians was 0.40±0.24 s/image(P<0.001).CONCLUSION The deep learning model of image classification combined with object detection exhibits a satisfactory diagnostic effect on a variety of SB lesions and their bleeding risks in CE images,which enhances the diagnostic efficiency of physicians and improves the ability of physicians to identify high-risk bleeding groups.

关键词： Artificial intelligence Deep learning Capsule endoscopy Image classification Object detection Bleeding risk

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METTL5 promotes gastric cancer progression via sphingomyelin metabolism

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World Journal of Gastrointestinal Oncology 2024年第5期16卷 1925-1946页

作者： Ya-Qiong zhang Jian Li Zhe Qin De-Ming Li Fang-Zhou Ye Song-Hua Bei Xiao-Hong zhang Li Feng Endoscopy Center Minhang Hospital Affiliated to Fudan UniversityShanghai 201100China

BACKGROUND The treatment of gastric cancer(GC)has caused an enormous social burden *** studies have reported that N6-methyladenosine(m6A)is closely related to tumor ***5 is a m6A methyltransferase that plays a pivotal role in maintaining the metabolic stability of ***,its aberrant regulation in GC has not been fully *** To excavate the role of METTL5 in the development of *** METTL5 expression and clinicopathological characteristics were analyzed via The Cancer Genome Atlas dataset and further verified via immunohistochemistry,western blotting and real-time quantitative polymerase chain reaction in tissue microarrays and clinical *** tumor-promoting effect of METTL5 on HGC-27 and AGS cells was explored in vitro by Cell Counting Kit-8 assays,colony formation assays,scratch healing assays,transwell assays and flow *** tumor-promoting role of METTL5 in vivo was evaluated in a xenograft tumor *** EpiQuik m6A RNA Methylation Quantification Kit was used for m6A ***,liquid chromatography-mass spectrometry was used to evaluate the association between METTL5 and sphingomyelin metabolism,which was confirmed by Enzyme-linked immunosorbent assay and rescue *** addition,we investigated whether METTL5 affects the sensitivity of GC cells to cisplatin via colony formation and transwell *** Our research revealed substantial upregulation of METTL5,which suggested a poor prognosis of GC *** METTL5 expression indicated distant lymph node metastasis,advanced cancer stage and pathological *** increased level of METTL5 correlated with a high degree of m6A ***5 markedly promotes the proliferation,migration,and invasion of GC cells in ***5 also promotes the growth of GC in animal ***5 knockdown resulted in significant changes in sphingomyelin metabolism,which implies that METTL5 may impact the development of GC via sphin

关键词： Gastric cancer METTL5 Sphingomyelin metabolism Cisplatin

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IPFA-Net: Important Points Feature Aggregating Net for Point Cloud Classification and Segmentation

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Chinese Journal of Electronics 2024年

作者： Jingya WANG Yu zhang Bin zhang Jinxiang XIA Weidong WANG School of Information and Software Engineering University of Electronic Science and Technology of China National Key Laboratory of Automotive Chassis Integration and Bionics Jilin University

This paper focuses on the problems of point cloud deep neural networks in classification and segmentation tasks, including losing important information during down-sampling, ignoring relationships among points when extracting features, and network performance being susceptible to the sparsity of point cloud. To begin with, this paper proposes a farthest point sampling(FPS)-important points sampling(F-IPS) method for down-sampling, which can preserve important information of point clouds and maintain the geometry of input data. Then, the local feature relation aggregating(LFRA) method is proposed for feature extraction, improving the network's ability to learn contextual information and extract rich local region features. Based on these methods, the important points feature aggregating net(IPFA-Net) is designed for point cloud classification and segmentation tasks. Furthermore, this paper proposes the multi-scale multi-density feature connecting(MMFC) method to reduce the negative impact of point cloud data sparsity on network performance. Finally, the effectiveness of IPFA-Net is demonstrated through experiments on ModelNet40, ShapeNet part, and ScanNet v2 datasets. IPFA-Net is robust to reducing the number of point clouds, with only a 3.3% decrease in accuracy under a 16-fold reduction of point number. In the part segmentation experiments, our method achieves the best segmentation performance for five objects.

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Review and prospect of floating car data research in transportation

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Journal of Traffic and Transportation Engineering(English Edition) 2024年

作者： Chi zhang Yuming Zhou Min zhang Bo Wang Yuhan Nie School of Highway， Chang'an University College of Transportation Engineering， Chang'an University

With the advancement of Intelligent Transportation Systems， floating car data， as a crucial source of transportation information， has garnered increasing attention for its applications and development directions within the context of massive traffic data. This study conducts an in-depth literature review analysis of floating car data in the transportation field based on the Web of Science (WOS) database from 2000 to 2023， employing bibliometric methods and knowledge graph technologies. The current research status was visually analyzed through the literature distribution by year， research regions and institutions， research hotspots， and literature clustering using the bibliometric tool CiteSpace. Three major research topics were identified based on the literature clustering analysis. A systematic review of key literature was conducted to address research challenges related to floating car sampling proportions and frequencies， and future research challenges and opportunities were proposed. The result shows an overall parabolic increase in publication volume， with research hotspots mainly focusing on mountainous cities， cluster analysis， machine learning， and deep learning. The three major research clusters include traffic flow state， traffic safety， and route planning. The optimal investment proportion for floating cars is determined to be 3-8%， and the sampling frequency significantly affects the accuracy of vehicle speed and heading angle information， while having a weaker impact on positional parameters. With the trend of large-scale Internet-connected vehicle deployment in the future， a massive amount of floating car data will be generated， prompting in-depth research on the fusion of heterogeneous data sources， including floating car data. Future research could focus on leveraging Transformer and Graph Neural Networks to explore spatiotemporal features of data， developing lightweight real-time floating car data processing algorithms， and constructing multimodal r

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Advances in intelligent mass spectrometry data processing technology for in vivo analysis of natural medicines

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Chinese Journal of Natural Medicines 2024年第10期22卷 900-913页

作者： CHEN Simian DAI Binxin zhang Dandan YANG Yuexin zhang Hairong zhang Junyu LU Di WU Caisheng Fujian Provincial Key Laboratory of Innovative Drug Target Research and State Key Laboratory of Cellular Stress Biology School of Pharmaceutical Sciences Xiamen University Xiamen Key Laboratory for Clinical Efficacy and Evidence-Based Research of Traditional Chinese Medicine Xiamen University

Natural medicines(NMs) are crucial for treating human diseases. Efficiently characterizing their bioactive components in vivo has been a key focus and challenge in NM research. High-performance liquid chromatography-high-resolution mass spectrometry(HPLC-HRMS) systems offer high sensitivity, resolution, and precision for conducting in vivo analysis of NMs. However, due to the complexity of NMs, conventional data acquisition, mining, and processing techniques often fail to meet the practical needs of in vivo NM analysis. Over the past two decades, intelligent spectral data-processing techniques based on various principles and algorithms have been developed and applied for in vivo NM analysis. Consequently, improvements have been achieved in the overall analytical performance by relying on these techniques without the need to change the instrument hardware. These improvements include enhanced instrument analysis sensitivity, expanded compound analysis coverage, intelligent identification, and characterization of nontargeted in vivo compounds, providing powerful technical means for studying the in vivo metabolism of NMs and screening for pharmacologically active components. This review summarizes the research progress on in vivo analysis strategies for NMs using intelligent MS data processing techniques reported over the past two decades. It discusses differences in compound structures, variations among biological samples, and the application of artificial intelligence(AI) neural network algorithms. Additionally, the review offers insights into the potential of in vivo tracking of NMs, including the screening of bioactive components and the identification of pharmacokinetic markers. The aim is to provide a reference for the integration and development of new technologies and strategies for future in vivo analysis of NMs.

关键词： Artificial Intelligence Data-acquisition Data-processing High-performance liquid chromatography–High-resolution mass spectrometry Metabolomics

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Improved Variable Forgetting Factor Proportionate RLS Algorithm with Sparse Penalty and Fast Implementation Using DCD Iterations

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China Communications 2024年第10期 16-27页

作者： Han Zhen zhang Fengrui zhang Yu Han Yanfeng Jiang Peng GNSS Research Center Wuhan University School of Information Science and Technology Shijiazhuang Tiedao University

The proportionate recursive least squares（PRLS） algorithm has shown faster convergence and better performance than both proportionate updating（PU） mechanism based least mean squares（LMS） algorithms and RLS algorithms with a sparse regularization term. In this paper, we propose a variable forgetting factor（VFF） PRLS algorithm with a sparse penalty, e.g., l1-norm, for sparse identification. To reduce the computation complexity of the proposed algorithm, a fast implementation method based on dichotomous coordinate descent（DCD） algorithm is also derived. Simulation results indicate superior performance of the proposed algorithm.

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A prognostic model of patients with pancreatic cancer based on four N^(6)-methyladenosine-related IncRNAs and analysis of related immune infiltration

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Genes & Diseases 2024年第4期11卷 109-112页

作者： Kaili Liao Yuhan Xu Bingying Lin Yuxuan Xie Qijun Yang Wenyige zhang Beining zhang Jiarong Wen Jingyi Wang Zimeng Li Yunqi Cheng Xiaozhong Wang Jiangxi Province Key Laboratory of Laboratory Medicine Jiangxi Provincial Clinical Research Center for Laboratory MedicineDepartment of Clinical LaboratoryThe Second Affiliated Hospital of Nanchang UniversityNanchangJiangxi 330006China Queen Mary College of Nanchang University NanchangJiangxi 330001China School of Public Health Nanchang UniversityNanchangJiangxi 330006China The Second Clinical Medical College Nanchang UniversityNanchangJiangxi 330006China The First Clinical Medical College of Nanchang University NanchangJiangxi 330006China

Pancreatic cancer is one of the most lethal malignant tumors in the *** advances in diagnosis and treatment,the five-year survival rate for pancreatic cancer patients remains only 9%.1 Pancreatic adenocarcinoma(PAAD)belongs to pancreatic cancer,which occupies 85%of the whole pancreatic cancer.2 Reversible modification of Ne-methyladenosine(m^(6)A)has been shown to be involved in cancer progression,resulting in up-regulation of oncogene expression or down-regulation of tumor-suppressing genes and may affect the prognosis of patients with pancreatic cancer.

关键词： patients cancer diagnosis

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Screened peptides from one-bead one-compound technique extend half-life of peptide drugs in circulation through binding to albumin

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Chinese Chemical Letters 2024年第3期35卷 384-388页

作者： Yi-Jing Li Lingze zhang Ming-Hao Pang Pei-Pei Yang Lu-Ming Guo Kuo zhang Da-Yong Hou Lei Wang Hao Wang Hui Cao State Key Laboratory for Advanced Metals and Materials School of Materials Science and EngineeringUniversity of Science and Technology BeijingBeijing 100083China CAS Center for Excellence in Nanoscience CAS Key Laboratory for Biomedical Effects of Nanomaterials NanosafetyNational Center for Nanoscience and Technology(NCNST)Beijing 100190China

Peptide drugs are known for their high biological ***,compared with small molecule drugs,peptide drugs are easily oxidized and hydrolyzed as well as short in ***,inspired by the long circulation of albumin in blood,we screened albumin binding peptides(ABPs)from a one-bead one-compound(OBOC)peptide library to increase the half-life of peptide *** displaying random peptides were screened using fluorescent labeled human serum *** beads with specific binding to albumin were isolated for *** selected ABPs can effectively bind to albumin,thus possessing the long circulation of *** dissociation constant(K_(D))of ABPs to albumin is up to 1×10^(-8)mol/*** one of ABPs(ABP2)was coupled to triptorelin,the circulation half-life of triptorelin in mice was significantly prolonged to 263.50 h much longer than that of triptorelin alone(179.07 h).In addition,the combination therapy using ABP-conjugated triptorelin and doxorubicin(DOX)can effectively inhibit the proliferation of tumor cells in *** OBOC screening strategy and resulting ABPs showed great potential for enhancing the delivery efficiency of peptide drugs.

关键词： One-bead one-compound Combinatorial library Albumin binding Drug delivery Triptorelin

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Dynamic analysis of beta oscillations in Parkinsonian neural networks with the pedunculopontine nucleus under optogenetic control

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Acta Mechanica Sinica 2024年第6期40卷 125-140页

作者： Yuzhi Zhao Honghui zhang Ying Yu Lin Du Zichen Deng School of Mathematics and Statistics Northwestern Polytechnical UniversityXi’an710072China School of Aeronautic Science and Engineering Beihang UniversityBeijing100191China School of Aeronautics Northwestern Polytechnical UniversityXi’an710072China

Clinical experiments have proven that the pedunculopontine nucleus(PPN)plays a crucial role in the modulation of beta oscillations in Parkinson’s disease(PD).Here,we propose a new computational framework by introducing the PPN and related synaptic connections to the classic basal ganglia-thalamo-cortical ***,the improved model can not only simulate the basic saturated and beta activities mentioned in previous studies but also produce the normal alpha rhythm that is much closer to physiological ***,the results show that Parkinsonian oscillation activities can be controlled and modulated by the connection strength between the PPN and the globus pallidus internal nucleus(GPi)and the subthalamic nucleus(STN),supporting the fact that PPN is overinhibited in ***,the internal mechanism underlying these state transitions is further explained from the perspective of ***,both deep brain stimulation(DBS)and optogenetic technology are considered effective in terms of abnormal *** when a low-frequency DBS is added to the PPN,beta oscillations can be suppressed,but it is excited again as the DBS’s frequency gradually increases to a larger *** results coincide with the experimental results that low-frequency stimulation of the PPN is effective,and verify the rationality of the ***,we show that optogenetic stimulation of the globus pallidus external(GPe)expressing excitatory channelrhodopsin(ChR2)can effectively inhibit beta oscillations,whereas exciting the STN and PPN has a limited *** results are consistent with experimental reports suggesting that the symptoms of PD’s movement disorder can be alleviated under the GPe-ChR2,but not STN-ChR2,*** the functional role of the PPN and the feasibility of optogenetic stimulation remain to be clinically explored,the results obtained help us understand the mechanisms of beta oscillations in PD.

关键词： Pedunculopontine nucleus Beta oscillations Optogenetic Deep brain stimulation Parkinson’s disease

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Structural Transformations and Multiferroic Properties of Bi_(1-x)Eu_(x)Fe_(0.95)Co_(0.05)O_(3)(x=0.05,0.10,0.15,and 0.20)

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Journal of Wuhan University of Technology(Materials Science) 2024年第2期39卷 315-319页

作者：梁修乾李永涛 LIU Liqing GUO Aiqian LI Jianda zhang Hongguang College of Science Nanjing University of Posts and TelecommunicationsNanjing 210023China College of Electronic Science and Engineering Nanjing University of Posts and TelecommunicationsNanjing 210023China

Bi_(1-x)Eu_(x)Fe_(0.95)Co_(0.05)O_(3 )(x=0.05,0.10,0.15,and 0.20) nanoparticles were prepared through the sol-gel *** structure,local electronic structure,magnetic and electric properties were systematically investigated.X-ray diffraction data show(104),(110) bimodal alignment and high angular migration,indicating that with the increase of Eu substitution at Bi site,the structure of BFO undergoes a continuous change in crystal *** hysteresis loop and the FC/ZFC curve show how magnetism varies with the size of the field and ***,the causes of magnetic changes were analyzed by studying SXAS and hysteresis loops.

关键词： magnetic materials XAS electric structure magnetic property

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