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Differences in Brain Structural Covariance Network Characteristics in Children and Adults With Autism Spectrum Disorder

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AUTISM RESEARCH 2021年第2期14卷 265-275页

作者： Cai, Suping wang, xuwen Yang, Fan Chen, Dihui Huang, Liyu Xidian Univ Sch Life Sci & Technol Xian 710071 Shaanxi Peoples R China

Systematically describing the structural topological configuration of human brain during development is an essential task. Autism spectrum disorder (ASD) represents a powerful challenge for psychiatry and neuroscience researchers. In this study, we investigated variations in the structural covariance network properties of 441 patients with ASD ranging in age from 7 to 45 years and in 426 age-matched healthy controls (HCs) using structural magnetic resonance neuroimaging from the ABIDE database. We applied a sliding window approach to study topological variation during development using comprehensive graph theoretical analysis. The main findings are as follows: (1) Cross-sectional trajectories of the network characteristics exhibited inverted U-shapes in both HCs and participants with ASD, with the latter exhibiting a 7-year delay in reaching the maximum value, (2) network resilience to targeted attacks peaked at 18 ' and 19 ' in the HCs and at 25 ' in the participants with ASD, and the weakest resilience occurred at age 7 ', (3) the HCs and participants with ASD exhibited normalized mean degree differences in the right amygdala, and (4) significant differences in the network characteristics were observed in the 18 ' age group at most of the densities analyzed. We used cross-sectional analysis to infer distinct neurodevelopmental trajectories in ASD in the brain structural connectome. Our findings are consistent with the notion that adolescence is a sensitive period of brain development with strong potential for brain plasticity, offering opportunities for environmental adaptation and social integration and for increasing vulnerability. ASD may be a product of susceptibility. Lay Summary We used cross-sectional analysis to preliminarily infer distinct neurodevelopmental trajectories in ASD in the brain structural connectome. The main findings are as follows: (1) Cross-sectional trajectories of the network characteristics exhibited inverted U-shapes in both HCs and pa

关键词： structure covariance network autism spectrum disorder sliding window analysis graph theoretical analysis brain development structural magnetic resonance neuroimaging

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A deep learning approach for identifying biomedical breakthrough discoveries using context analysis

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SCIENTOMETRICS 2021年第7期126卷 5531-5549页

作者： wang, Xue Yang, Xuemei Du, Jian wang, xuwen Li, Jiao Tang, Xiaoli Chinese Acad Med Sci & Peking Union Med Coll Inst Med Informat & Lib Beijing 100005 Peoples R China Peking Univ Natl Inst Hlth Data Sci Beijing 100191 Peoples R China

Breakthrough research in scientific fields usually comes as a manifestation of major development and advancement. These advances build to an epiphany where new ways of thinking about a problem become possible. Identifying breakthrough research can be useful for cultivating and funding further innovation. This article presents a new method for identifying scientific breakthroughs from research papers based on cue words commonly associated with major advancements. We looked for specific terms signifying scientific breakthroughs in citing sentences to identify breakthrough articles. By setting a threshold for the number of citing sentences ("citances") with breakthrough cue words that peer scholars often use when evaluating research, we identified articles containing breakthrough research. We call this approach the "others-evaluation" process. We then shortlisted candidates from the selected articles based on the authors' evaluations of their own research, found in the abstracts. This we call the "self-evaluation" process. Combining the two approaches into a dual "others-self" evaluation process, we arrived at a sample of 237 potential breakthrough articles, most of which are recommended by the Faculty Opinions. Based on the breakthrough articles identified, using SVM, TextCNN, and BERT to train the models to identify abstracts with breakthrough evaluations. This automatic identification model can greatly simplify the process of others-self-evaluation process and promote identifying breakthrough research.

关键词： Deep learning Context analysis Breakthrough discoveries Breakthrough identification Citances

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真性小眼球PRSS56基因突变与临床特征研究

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眼科 2025年第1期34卷 27-33页

作者：陶靖郝洁沈人娟傅语潇李姣王序文首都医科大学附属北京同仁医院北京同仁眼科中心眼科学与视觉科学北京市重点实验室北京100730 中国医学科学院/北京协和医学院医学信息研究所北京100020

目的研究中国真性小眼球患者PRSS56基因突变的遗传和临床特征,揭示基因型与表型之间的相关性。设计回顾性病例系列。研究对象2003-2023年在北京同仁医院眼科就诊并随访的40个真性小眼球家系。方法回顾对患者和家系成员进行的详细眼科检... 详细信息

目的研究中国真性小眼球患者PRSS56基因突变的遗传和临床特征,揭示基因型与表型之间的相关性。设计回顾性病例系列。研究对象2003-2023年在北京同仁医院眼科就诊并随访的40个真性小眼球家系。方法回顾对患者和家系成员进行的详细眼科检查资料。对40个家系中有血样的51例患者及42例家系成员采用全外显子组测序(WES)分析PRSS56基因编码区和相邻内含子区,并进行生物信息学分析和致病性预测。基因型与表型的发生率统计分析采用SPSS27.0和R 4.4.1软件进行。主要指标眼部检查结果、突变基因型、闭角型青光眼(ACG)及葡萄膜渗漏综合征(UES)并发症的发生情况。结果在这40个真性小眼球家系中,检测出15个与PRSS56基因突变相关的家系(其中先证者15例,患病家属5例),检出率为37.50%(15/40)。共发现16种PRSS56基因突变,包括3种新突变[c.494dupG(***167Gly)、c.340dupG(***115Gly)、c.407C>T(***136Val)]和13种已报道的突变。其中c.1066dupC突变频率为53.33%(8/15),是本队列中最常见的突变。PRSS56基因突变的真性小眼球呈现视力低下、眼轴短、前房浅、视盘拥挤、视网膜血管扩张迂曲、黄斑区视网膜皱褶等临床特征。首诊年龄>40岁组的平均巩膜厚度更厚,平均中央前房深度更浅,发生ACG和UES的比例更高(P均<0.05)。c.1066dupC高频突变携带组呈现眼前节更短的趋势。结论本研究阐述了中国真性小眼球PRSS56基因突变与临床特征及其相关性,扩展了PRSS56基因的突变谱,加深了真性小眼球基因型和表型关联的认识,为该病的精确诊疗和预后管理奠定了更加完善的理论基础。

关键词：真性小眼球 PRSS56基因突变

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Exploring the prominent performance of CX-4945 derivatives as protein kinase CK2 inhibitors by a combined computational study

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MOLECULAR BIOSYSTEMS 2014年第5期10卷 1196-1210页

作者： wang, xuwen Pan, Peichen Li, Youyong Li, Dan Hou, Tingjun Soochow Univ Inst Funct Nano & Soft Mat FUNSOM Suzhou 215123 Jiangsu Peoples R China Soochow Univ Collaborat Innovat Ctr Suzhou Nano Sci & Technol Suzhou 215123 Jiangsu Peoples R China Zhejiang Univ Coll Pharmaceut Sci Hangzhou 310058 Zhejiang Peoples R China

Protein kinase CK2, also known as casein kinase II, is related to various cellular events and is a potential target for numerous cancers. In this study, we attempted to gain more insight into the inhibition process of CK2 by a series of CX-4945 derivatives through an integrated computational study that combines molecular docking, molecular dynamics (MD) simulations, and binding free energy calculations. Based on the binding poses predicted by molecular docking, the MD simulations were performed to explore the dynamic binding processes for ten selected inhibitors. Then, both Molecular Mechanics/Poisson Boltzmann Surface Area (MM/PBSA) and Molecular Mechanics/Generalized Born Surface Area (MM/GBSA) techniques were employed to predict the binding affinities of the studied systems. The predicted binding energies of the selected inhibitors correlate well with their experimental activities (r(2) = 0.78). The van der Waals term is the most favorable component for the total energies. The free energy decomposition on a per residue basis reveals that the residue K68 is essential for the electrostatic interactions between CK2 and the studied inhibitors and numerous residues, including L45, V53, V66, F113, M163 and I174, play critical roles in forming van der Waals interactions with the inhibitors. Finally, a number of new derivatives were designed and the binding affinity and the predicted binding free energies of each designed molecule were obtained on the basis of molecular docking and MM/PBSA. It is expected that our research will benefit the future rational design of novel and potent inhibitors of CK2.

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The role of apparent diffusion coefficient in the grading of adult isocitrate dehydrogenase-mutant astrocytomas: relationship with the Ki-67 proliferation index

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ACTA RADIOLOGICA 2024年第5期65卷 489-498页

作者： She, Yingxia Liu, Xianwang Jiang, Jian wang, xuwen Niu, Qian Zhou, Junlin Lanzhou Univ Second Hosp Radiol Dept Lanzhou Peoples R China Lanzhou Univ Second Hosp Key Lab Med Imaging Gansu Prov Lanzhou Peoples R China Lanzhou Univ Second Hosp Gansu Int Sci & Technol Cooperat Base Med Imaging Lanzhou Peoples R China Lanzhou Univ Second Hosp Pathol Dept Lanzhou Peoples R China Lanzhou Univ Second Hosp Dept Radiol Cuiyingmen 82 Lanzhou 730030 Peoples R China

Background: The grading of adult isocitrate dehydrogenase (IDH)-mutant astrocytomas is a crucial prognostic factor. Purpose: To investigate the value of conventional magnetic resonance imaging (MRI) features and apparent diffusion coefficient (ADC) in the grading of adult IDH-mutant astrocytomas, and to analyze the correlation between ADC and the Ki-67 proliferation index. Material and Methods: The clinical and MRI data of 82 patients with adult IDH-mutant astrocytoma who underwent surgical resection and molecular genetic testing with IDH and 1p/19q were retrospectively analyzed. The conventional MRI features, ADC(min), ADC(mean), and nADC of the tumors were compared using the Kruskal-Wallis single factor ANOVA and chi-square tests. Receiver operating characteristic (ROC) curves were drawn to evaluate conventional MRI and ADC accuracy in differentiating tumor grades. Pearson correlation analysis was performed to determine the correlation between ADC and the Ki-67 proliferation index. Results: The difference in enhancement, ADC(min), ADC(mean), and nADC among WHO grade 2, 3, and 4 tumors was statistically significant (all P <0.05). ADC(min) showed the preferable diagnostic accuracy for grading WHO grade 2 and 3 tumors (AUC=0.724, sensitivity=63.4%, specificity=80%, positive predictive value (PPV)=62.0%;negative predictive value (NPV)=82.5%), and distinguishing grade 3 from grade 4 tumors (AUC=0.764, sensitivity=70%, specificity=76.2%, PPV=75.0%, NPV=71.4%). Enhancement + ADC model showed an optimal predictive accuracy (grade 2 vs. 3: AUC = 0.759;grade 3 vs. 4: AUC = 0.799). The Ki-67 proliferation index was negatively correlated with ADC(min), ADC(mean), and nADC (all P <0.05), and positively correlated with tumor grade. Conclusion: Conventional MRI features and ADC are valuable to predict pathological grading of adult IDH-mutant astrocytomas.

关键词： Apparent diffusion coefficient astrocytomas isocitrate dehydrogenase-mutant Ki-67 proliferation index

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Effect of the Amount of Channel Black on Underwater Property of PU Material

Effect of the Amount of Channel Black on Underwater Property...

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7th International Conference on MEMS, NANO and Smart Systems (ICMENS 2011)

作者： wang, xuwen Zhang, Yongbing Lin, Xinzhi Sun, Yingfu Luoyang Ship Mat Res Inst Luoyang Peoples R China

ISBN: (纸本)9783037853122

Effect of the amount of Channel Black on underwater property of PU material is researched by adding Channel Black into PU material. The results show that the amount of Channel Black has most effect on underwater property of PU material. In one atmospheric pressure, the underwater property of PU material is worst when the amount of Channel Black is 60, while the underwater properties are not evident when the amount of channel is 30 and 45. In lower underwater pressure, effect of the amount of Channel Black on underwater property of PU material is almost difference. In higher underwater pressure, the underwater property of PU material is best when the amount of Channel Black is 45, while 30 is second, and 60 is lowest.

关键词： Channel Black PU Underwater Property

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Study on Mechanical Behavior of Masonry Wall in School Building Reinforced by CFRP

Study on Mechanical Behavior of Masonry Wall in School Build...

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International Conference on Materials Engineering and Mechanical Automation (MEMA 2013)

作者： Lin, Hong Yang, Zhao wang, xuwen Ke, Xiang Wuhan Univ Technol Design & Res Inst Wuhan 430070 Peoples R China Wuhan Univ Sci & Technol Inst Urban Construct Wuhan Peoples R China

ISBN: (纸本)9783037859018

CFRP is a new kind of building materials popularly used in structure strengthening. In order to study the reinforcement technique for masonry walls of school buildings, the walls with window opening strengthened by CFRP were studied in the paper. Based on the experiment result, the finite element simulation and theoretical calculation analysis were done to study the mechanical behavior and shear capacity of the wall with window opening reinforced by CFRP. The CFRP pasted at the corner of window opening were proved to be effectively in improving shear capacity of the walls, and simple calculation formulas of shear capacity were provided in the paper, which proved to be accurate.

关键词： CFRP Masonry structure Mechanical behavior Shear capacity

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Physical information-enhanced graph neural network for predicting phase separation

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Chinese Physics B 2024年第7期33卷 278-283页

作者：张亚强王煦文王雅楠郑文 Institute of Public-Safety and Big Data College of Computer Science and Technology(College of Data Science)Taiyuan University of TechnologyJinzhong 030600China Shanxi Engineering Research Centre for Intelligent Data Assisted Treatment Changzhi Medical CollegeChangzhi 046000China Innovation Academy for Microsatellites of Chinese Academy of Sciences Shanghai 200050China

Although phase separation is a ubiquitous phenomenon, the interactions between multiple components make it difficult to accurately model and predict. In recent years, machine learning has been widely used in physics simulations. Here,we present a physical information-enhanced graph neural network(PIENet) to simulate and predict the evolution of phase separation. The accuracy of our model in predicting particle positions is improved by 40.3% and 51.77% compared with CNN and SVM respectively. Moreover, we design an order parameter based on local density to measure the evolution of phase separation and analyze the systematic changes with different repulsion coefficients and different Schmidt *** results demonstrate that our model can achieve long-term accurate predictions of order parameters without requiring complex handcrafted features. These results prove that graph neural networks can become new tools and methods for predicting the structure and properties of complex physical systems.

关键词： graph neural network phase separation machine learning dissipative particle dynamics

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Mining a large Chinese-English corpus from web

Mining a large Chinese-English corpus from web

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2012 IEEE Symposium on Electrical and Electronics Engineering, EEESYM 2012

作者： wang, xuwen Lin, Ye wang, Xiaojie Tan, Yongmei Center for Intelligence Science and Technology Beijing University of Posts and Telecommunications Beijing China

ISBN: (纸本)9781467323659

Bilingual parallel corpora provide rich source of translate information for tasks such as cross-language information retrieval and data-driven machine translation systems. However, they are often scarce resources: limited in size, language coverage and language register. Researchers have to struggle to transfer and adapt the available technologies because only some small scale corpora are suitable. In this paper we introduce a large parallel corpus of Chinese and English constructed by crawling and processing bilingual web documents from Internet. It currently contains about 300,000 parallel sentence pairs. The tools and methodology used in this collection project are also described. In a cross-language retrieval task we experimented with this self-constructed corpus to improve the quality of query translation, so as to achieve better retrieval performance. © 2012 IEEE.

关键词： Search engines

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JOINTS RELATION INFERENCE NETWORK FOR SKELETON-BASED ACTION RECOGNITION 26

JOINTS RELATION INFERENCE NETWORK FOR SKELETON-BASED ACTION ...

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26th IEEE International Conference on Image Processing (ICIP)

作者： Ye, Fanfan Tang, Huiming wang, xuwen Liang, Xiao Zhejiang Univ Coll Informat Sci & Elect Engn Hangzhou Peoples R China

ISBN: (纸本)9781538662496

Recently, the graph convolutional networks based methods have achieved remarkable performance in skeleton-based action recognition. However, current methods do not make full use of the topology of the skeleton graph, because they set and fixed the relation of skeleton joints or adjacency matrix for all input samples manually. In order to solve the problem, we design an end-to-end architecture consisting of joints relation inference network (JRIN) and skeleton graph convolutional network (SGCN). JRIN can aggregate spatial-temporal feature of every two joints globally, then infer the optimal relation between every two joints automatically. These relations of joints is quantified as the optimal adjacency matrices. Then SGCN will take the optimal matrices to do the final action recognition. During training, special initialization and alternate training strategies are proposed to optimize the model. Our method achieves very competitive performance on widely used NTU-RGB+D and Kinetics datasets.

关键词： Action Recognition Relation Inference Graph Convolutional Network Skeleton

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