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Physical information-enhanced graph neural network for predicting phase separation

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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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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LDA BASED PSEUDO RELEVANCE FEEDBACK FOR CROSS LANGUAGE INFORMATION RETRIEVAL

LDA BASED PSEUDO RELEVANCE FEEDBACK FOR CROSS LANGUAGE INFOR...

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2nd IEEE International Conference on Cloud Computing and Intelligent Systems (CCIS)

作者： wang, xuwen Zhang, Qiang wang, Xiaojie Sun, Yueping Beijing Univ Posts & Telecommun Beijing 100876 Peoples R China State Grid Elect Power Res Inst Beijing 100192 Peoples R China

ISBN: (纸本)9781467318556;9781467318570

This paper introduced a LDA-based pseudo relevance feedback (PRF) model for cross language information retrieval. To validate the performance of PRF techniques in CLIR task, we conducted cross language query expansion experiments based on a self-constructed CLIR system, the LDA-based PRF model was applied before or after the query translating process, namely the pre-translation-PRF, the post-translation-PRF, and the combined-PRF strategy. We also compared this model with the classical VSM-based-PRF algorithm. Experiment results showed that the proposed LDA-based PRF method was effective for improving the performance of CLIR.

关键词： Pseudo relevance feed back Latent Dirichlet Allocation (LDA) Query expansion Vector Space Model (VSM) Cross language information retrieval

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An OPTICS clustering-based anomalous data filtering algorithm for condition monitoring of power equipment 1

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3rd International Conference on Data Analytics for Renewable Energy Integration, DARE 2015

作者： Zhang, Qiang wang, xuwen wang, Xiaojie State Grid Electric Power Research Institute Beijing100192 China Institute of Medical Information CAMS & PUMC Beijing100020 China Beijing University of Posts and Telecommunications Beijing100876 China

ISBN: (数字)9783319274300

ISBN: (纸本)9783319274294

In allusion to the widespread anomalous data in substation primary equipment condition monitoring, this paper proposes an OPTICS (Ordering Points To Identify the Clustering Structure) clustering-based condition monitoring anomalous data filtering algorithm. Through the characteristic analysis of historical primary equipment condition monitoring data, an anomalous data filtering mechanism was built based on density clustering. The effectiveness of detecting anomalous data was verified through the experiments on one 110 kV substation equipment transformer oil chromatography and the GIS (Gas Insulated Substation) SF6 density micro water. Compared with traditional anomalous data detection algorithms, the OPTICS Clustering-based algorithm has shown significant performance in identifying the features of anomalous data as well as filtering condition monitoring anomalous data. Noises were reduced effectively and the overall reliability of condition monitoring data was also improved. © Springer International Publishing Switzerland 2015.

关键词： Data mining

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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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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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Identification of the Metabolites in Rat Urine after Oral Administration and Elucidation of the Metabolic Process of Naozhenning Granule Using LC-MS

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JOURNAL OF CHROMATOGRAPHIC SCIENCE 2020年第9期58卷 804-813页

作者： Li, Rongrong Liu, Yanzhi Liu, Haixia Wei, Chunhong wang, Jiang Qin, Xuemei wang, xuwen Li, Zhenyu Shanxi Univ Modern Res Ctr Tradit Chinese Med Taiyuan 030006 Peoples R China Shanxi Zhendong Ante Biol Pharmaceut Co Ltd Jinzhong 030600 Peoples R China

Naozhenning (NZN) granule, a Chinese herbal formula, is widely used to treat craniocerebral trauma and promote functional recovery. In our previous study, the chemical components, as well as the serum metabolites in the male Sprague-Dawley rats of the NZN granule after oral administration were characterized. In this study, the urine metabolites in the male Sprague-Dawley rats were further investigated by ultrahigh-performance liquid chromatography-Q Exactive hybrid quadrupole-Orbitrap high-resolution accurate mass spectrometry. In order to identify the urine metabolites comprehensively, three sample preparation methods were used, including solid-phase extraction, protein precipitation method and solvent partition. Based on the accurate molecular weight and the fragmentation information from the MS spectra, a total of 76 urine metabolites were identified, which including 17 prototypes and 59 metabolites. The results showed that the detected urine metabolites were different for the different pretreatment methods, as some metabolites could only be detected in the particular pretreatment method. In addition, the metabolic processes of the components from NZN granule to the serum and urine were also elucidated and discussed. The results will provide useful information for further studying the relationship between the chemical components and pharmacological activity of NZN granule.

关键词： Metabolites

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Binding affinity and dissociation pathway predictions for a series of USP7 inhibitors with pyrimidinone scaffold by multiple computational methods

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PHYSICAL CHEMISTRY CHEMICAL PHYSICS 2020年第10期22卷 5487-5499页

作者： wang, Zhe wang, xuwen Kang, Yu Zhong, Haiyang Shen, Chao Yao, Xiaojun Cao, Dongsheng Hou, Tingjun Zhejiang Univ Coll Pharmaceut Sci Hangzhou 310058 Zhejiang Peoples R China Macau Univ Sci & Technol Macau Inst Appl Res Med & Hlth State Key Lab Qual Res Chinese Med Ave Wai Long Taipa Macao Peoples R China Cent South Univ Xiangya Sch Pharmaceut Sci Changsha 410013 Hunan Peoples R China

Ubiquitin specific protease 7 (USP7) has attracted increasing attention because of its multifaceted roles in different tumor types. The crystal structures of USP7-inhibitor complexes resolved recently provide reliable models for computational structure-based drug design (SBDD) towards USP7. How to accurately estimate USP7-ligand binding affinity is quite critical to guarantee the reliability of SBDD. In this study, we assessed the reliability of multiple computational methods to the binding affinity prediction for a series of USP7 inhibitors with the pyrimidinone scaffold, including molecular docking scoring, MM/PB(GB)SA, and umbrella sampling (US). It was found that the accuracy of the evaluated computational methods for binding affinity prediction follows the order: US-based method > MM/PB(GB)SA > Glide XP scoring. The calculation results demonstrate that incorporating protein flexibility through induced-fit docking or ensemble docking cannot improve the performance of the Glide scoring based on rigid-receptor docking. For the MM/PB(GB)SA methods, the choice of the protein structure and the calculation procedure has a marked impact on the predictions. More importantly, we discovered for the first time that there are significant differences in the dissociation pathways of strong-binding inhibitors and weak-binding inhibitors of USP7, which may be used as a new criterion to judge whether an inhibitor is a strong binder or not. It is expected that our work can provide valuable guidance on the design and discovery of potent USP7 inhibitors.

关键词： Computational methods

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PEcnv: accurate and efficient detection of copy number variations of various lengths

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BRIEFINGS IN BIOINFORMATICS 2022年第5期23卷 bbac375-bbac375页

作者： wang, xuwen Xu, Ying Liu, Ruoyu Lai, Xin Liu, Yuqian wang, Shenjie Zhang, Xuanping wang, Jiayin Xi An Jiao Tong Univ Sch Comp Sci & Technol Xian Peoples R China Xi An Jiao Tong Univ Sch Comp Sci & Technol Med Informat Xian Peoples R China

Copy number variation (CNV) is a class of key biomarkers in many complex traits and diseases. Detecting CNV from sequencing data is a substantial bioinformatics problem and a standard requirement in clinical practice. Although many proposed CNV detection approaches exist, the core statistical model at their foundation is weakened by two critical computational issues: (i) identifying the optimal setting on the sliding window and (ii) correcting for bias and noise. We designed a statistical process model to overcome these limitations by calculating regional read depths via an exponentially weighted moving average strategy. A one-run detection of CNVs of various lengths is then achieved by a dynamic sliding window, whose size is self-adopted according to the weighted averages. We also designed a novel bias/noise reduction model, accompanied by the moving average, which can handle complicated patterns and extend training data. This model, called PEcnv, accurately detects CNVs ranging from kb-scale to chromosome-arm level. The model performance was validated with simulation samples and real samples. Comparative analysis showed that PEcnv outperforms current popular approaches. Notably, PEcnv provided considerable advantages in detecting small CNVs (1 kb-1 Mb) in panel sequencing data. Thus, PEcnv fills the gap left by existing methods focusing on large CNVs. PEcnv may have broad applications in clinical testing where panel sequencing is the dominant strategy.

关键词： genomics sequencing data analysis variant detection copy number variation (CNV) exponentially weighted moving average clinical panel sequencing

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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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