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Application of synchrotron source based DEI method in guinea pig cochleae imaging

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Progress in Natural Science:Materials International 2007年第1期17卷 59-67页

作者： YIN Hongxia, LIU Bo, GAO Xin, GAO Xiulai and LUO Shuqian ( College of biomedical engineering, capital university of {4. Sciences, {5. 100069, china Department of Anatomy, capital university of {4. Sciences, {5. 100069, china) College of biomedical engineering Capital University of Medical Sciences Beijing 100069 China Department of Anatomy Capital University of Medical Sciences Beijing 100069 China

Hard X-ray diffraction enhanced imaging (DEI), which is based on a synchrotron source and monochromator-analyzer-crystal system, is an effective method for imaging X-ray phase shift. Utilizing an analyzer crystal with high angular sensitivity of micro-radian, DEI can measure the transmitted, refracted and scattered X-rays when projecting onto a sample. It dramatically improves the contrast and spatial resolution of the resultant images. At the topography station of beijing Synchrotron Radiation Facilities (BSRF), we implemented DEI method in guinea pig cochleae imaging and acquired a series of DEI images. Based on these images, the apparent absorption and refraction images were calculated. The DEI images revealed the holistic spiral structures and inner details of guinea pig cochleae clearly, even including the structures at the cellular level, such as the static cilia of hairy cells and the limbus of Hansen cell. Due to the advantages of high contrast, high spatial resolution and distinct edge-enhanced effect, DEI method promises extensive applications in biology, medicine and clinic in the near future.

关键词： diffraction enhanced imaging hard X-ray imaging phase-contrast imaging cochlea micro-structure synchrotron source.

A novel model-free approach for reconstruction of time-delayed gene regulatory networks

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中国科学：生命科学英文版 2006年第2期49卷 190-200页

作者： JIANG Wei1,2, LI Xia1,2,3,4. GUO Zheng1,2,3, LI Chuanxing1, WANG Lihong1 & RAO Shaoqi1,5.1. Department of Bioinformatics, Harbin medical university, Harbin 15.086, china 2. Department of Computer Science, Harbin institute of Technology, Harbin 15.080, china 3. School of Life Science and Technology, Tongji university, Shanghai 200092, china 4. biomedical engineering institute, capital university of medical Sciences, beijing 10005., china 5. Departments of Cardiovascular Medicine and Molecular Cardiology, Cleveland Clinic Foundation, Cleveland, Ohio 4.195. USA Department of Bioinformatics Harbin Medical University Harbin 150086 China Department of Computer Science Harbin Institute of Technology Harbin 150080 China School of Life Science Technology Tongji University Shanghai 200092 China biomedical engineering institute Capital University of Medical Sciences Beijing 100054 China Departments of Cardiovascular Medicine Molecular Cardiology Cleveland Clinic Foundation Cleveland Ohio 44195 USA

Reconstruction of genetic networks is one of the key scientific challenges in functional genomics. This paper describes a novel approach for addressing the regulatory dependencies be-tween genes whose activities can be delayed by multiple units of time. The aim of the proposed ap-proach termed TdGRN (time-delayed gene regulatory networking) is to reversely engineer the dy-namic mechanisms of gene regulations, which is realized by identifying the time-delayed gene regu-lations through supervised decision-tree analysis of the newly designed time-delayed gene expres-sion matrix, derived from the original time-series microarray data. A permutation technique is used to determine the statistical classification threshold of a tree, from which a gene regulatory rule(s) is ex-tracted. The proposed TdGRN is a model-free approach that attempts to learn the underlying regula-tory rules without relying on any model assumptions. Compared with model-based approaches, it has several significant advantages: it requires neither any arbitrary threshold for discretization of gene transcriptional values nor the definition of the number of regulators (k). We have applied this novel method to the publicly available data for budding yeast cell cycling. The numerical results demonstrate that most of the identified time-delayed gene regulations have current biological knowledge supports.

关键词： gene regulatory networks, time delayed, decision tree.

Information extraction and CT reconstruction of liver images based on diffraction enhanced imaging

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Progress in Natural Science:Materials International 2009年第8期19卷 955-962页

作者： Chunhong Hua,b, Tao Zhao a, Lu Zhanga, Hui Lia, Xinyan Zhao c, Shuqian Luoa, a College of biomedical engineering, capital medical {4., {5. 100069, china b National Laboratory of Pattern Recognition, institute of Automation, Chinese Academy of Sciences, {5. 100080, china c Liver Research Center, {5. Friendship Hospital, capital medical {4.,{14., china [a]College of biomedical engineering Capital Medical University Beijing 100069 China [b]National Laboratory of Pattern Recognition Institute of Automation Chinese Academy of Sciences Beijing 100080 China [c]Liver Research Center Beijing Friendship Hospital Capital Medical University Beijing 100050 China

X-ray phase-contrast imaging (PCI) is a new emerging imaging technique that generates a high spatial resolution and high contrast of biological soft tissues compared to conventional radiography. Herein a biomedical application of diffraction enhanced imaging (DEI) is presented. As one of the PCI methods, DEI derives contrast from many different kinds of sample information, such as the sample’s X-ray absorption, refraction gradient and ultra-small-angle X-ray scattering (USAXS) properties, and the sample information is expressed by three parametric images. Combinedwith computed tomography (CT), DEI-CT can produce 3D volumetric images of the sample and can be used for investigating micro-structures of biomedical samples. Our DEI experiments for liver samples were implemented at the topography station of beijing Synchrotron Radiation Facility (BSRF). The results show that by using our provided information extraction method and DEI-CT reconstruction approach, the obtained parametric images clearly display the inner structures of liver tissues and the morphology of blood vessels. Furthermore, the reconstructed 3D view of the liver blood vessels exhibits the micro blood vessels whose minimum diameter is on the order of about tens of microns, much better than its conventional CT reconstruction at a millimeter resolution. In conclusion, both the information extraction method and DEI-CT have the potential for use in biomedical micro-structures analysis.

关键词： Diffraction enhanced imaging Computed tomography Information extraction X-ray Liver

An atlas-based fuzzy connectedness method for automatic tissue classification in brain MRI

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Progress in Natural Science:Materials International 2006年第10期16卷 1106-1110页

作者： ZHOU Yongxin and BAI Jing (Department of biomedical engineering, Tsinghua university, beijing 100084.{4.) [a]Department of biomedical engineering Tsinghua University Beijing China

A framework incorporating a subject-registered atlas into the fuzzy connectedness (FC) method is proposed for the automatic tissue classification of 3D images of brain MRI. The pre-labeled atlas is first registered onto the subject to provide an initial approximate segmentation. The initial segmentation is used to estimate the intensity histograms of gray matter and white matter. Based on the estimated intensity histograms, multiple seed voxels are assigned to each tissue automatically. The normalized intensity histograms are utilized in the FC method as the intensity probability density function (PDF) directly. Relative fuzzy connectedness technique is adopted in the final classification of gray matter and white matter. Experimental results based on the 20 data sets from IBSR are included, as well as comparisons of the performance of our method with that of other published methods. This method is fully automatic and operator-independent. Therefore, it is expected to find wide applications, such as 3D visualization, radiation therapy planning, and medical database construction.

关键词： fuzzy connectedness atlas-based segmentation brain tissue classification MR1.

A normalized thoracic coordinate system for atlas mapping in 3D CT images

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Progress in Natural Science:Materials International 2008年第1期18卷 111-117页

作者： Hongkai Wang,Jing Bai*,Yonghong Zhang Department of biomedical engineering,Tsinghua university,beijing 100084.{4. Department of biomedical engineering Tsinghua University Beijing 100084 China

In this paper,a normalized thoracic coordinate system(NTCS)is defined for rapidly mapping the 4. thoracic organ atlas into indi- vidual CT volume *** coordinate system is defined based on the thoracic *** coordinate values are normalized by the size of the individual thorax so that this coordinate system is universal to different *** compensating the respiratory motion of the organs,a 4. dynamic torso atlas is introduced.A method for mapping this dynamic atlas into the individual image using the NTCS is also *** this method,the dynamic atlas was mapped into the clinical thoracic CT images and rough positions of the organs were found *** NTCS-based 4. atlas mapping method may provide a novel way for estimating the thoracic organ positions in low-resolution molecular imaging modalities,as well as in modern 4. medical images.

关键词： Atlas mapping Registration Segmentation Molecular imaging

Urotensin Ⅱ accelerates cardiac fibrosis and hypertrophy of rats induced by isoproterenol

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Acta Pharmacologica Sinica 2007年第1期28卷 36-43页

作者： Yong-gang ZHANG~(2,5. Yu-guang LI~2 Bao-guo LIU~3 Rui-hong WEI~2 Dong-ming WANG~2 Xue-rui TAN~2 Ding-fang BU~4.Yong-zheng PANG~4.Chao-shu TANG~4. Department of Cardiovascular Diseases,First Affiliated Hospital,Shantou university medical College,Shantou 5.5.4.,china 3 The Affiliated Hospital,medical School of Hebei university of engineering,Hebei 05.029,china,4.institute of Cardiovascular Research,Peking university First Hospital,beijing 100034.china Department of Cardiovascular Diseases First Affiliated Hospital Shantou University Medical College Shantou China The Affiliated Hospital Medical School of Hebei University of Engineering Hebei China institute of Cardiovascular Research Peking University First Hospital Beijing China

Aim:To study whether urotensin II（UII）,a potent vasoconstrictive peptide,isinvolved in the development of cardiac hypertrophy and fibrogenesis of ratsinduced by isoproterenol（ISO）.Methods:Thirty male Wistar rats were randomlydivided into 3 *** 1 was the healthy control group,group 2 was the ISOgroup,and group 3 was the ISO+UII *** groups 2 and 3,ISO(5.mg-kg-1.d-1)wasgiven（sc）once daily for 7 *** 3 was also given UII in the first day [3 nmol/kg（5.g/kg）,iv],followed by sc（1.5.μg/kg）twice *** 1 received 0.9% *** receptor（UT）mRNA expression was determined by *** contents ofUII and angiotensin II（Ang II）were determined by *** vitro,the effects of UII on DNA/collagen synthesis of cardiac fibroblasts were deter-mined by [3H]thymidine/[3H]proline ***:The ratio of heartweight/body weight,plasma lactate dehydrogenase activity,myocardialmalondialdehyde and hydroxyproline concentration increased significantly in theISO group,as well as UT mRNA expression,plasma and cardiac UII and ventricu-lar Ang II,compared with the control group（P5.10～9-5.10-7mol/L UII stimulated[3H]thymidine/[3H]proline incorporation into cardiac fibroblasts in a dose-dependent manner（P<0.01）.Conclusion:These results suggest that UII was involved in the development ofcardiac fibrosis and hypertrophy by synergistic effects with ISO.

关键词： cardiac remodeling cardiac fibrosis GPR14.receptor urotensin II collagen

EFFECTS OF PARENT ARTERY SEGMENTATION AND ANEURISMALWALL ELASTICITY ON PATIENT-SPECIFIC HEMODYNAMIC SIMULATIONS

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Journal of Hydrodynamics 2011年第5期23卷 660-668页

作者： CHEN Jia-liang DING Guang-hong YANG Xin-jian LI Hai-yun Department of Mechanics and engineering Science Fudan University Shanghai 200433 China beijing institute of Neurosurgery Beijing 100050 China Department of biomedical engineering Capital Medical University Beijing 100050 China

It is well known that hemodynamics and wall tension play an important role in the formation, growth and rupture of aneurysms. In the present study, the authors investigated the influence of parent artery segmentation and aneurismal-wall elasticity on patient-specific hemodynamic simulations with two patient-specific cases of cerebral aneurysms. Realistic models of the aneurysms were constructed from 3-D angiography images and blood flow dynamics was studied under physiologically representative waveform of inflow. For each aneurysm three computational models were constructed： Model 1 with more extensive upstream parent artery with the rigid arterial and aneurismal wall, Model 2 with the partial upstream parent artery with the elastic arterial and aneurismal wall, Model 3 with more extensive upstream parent artery with the rigid wall for arterial wall far from the aneurysm and the elastic wall for arterial wall near the aneurysm. The results show that Model 1 could predict complex intra-aneurismal flow patterns and wall shear stress distribution in the aneurysm, but is unable to give aneurismal wall deformation and tension, Model 2 demonstrates aneurismal wall deformation and tension, but fails to properly model inflow pattern contributed by the upstream parent artery, resulting in local misunderstanding Wall Shear Stress （WSS） distribution, Model 3 can overcome limitations of the former two models, and give an overall and accurate analysis on intra-aneufismal flow patterns, wall shear stress distribution, aneurismal-wall deformation and tension. Therefore we suggest that the proper length of extensive upstream parent artery and aneurismal-wall elasticity should be considered carefully in establishing computational model to predict the intra-aneurismal hemodynamic and wall tension.

关键词： cerebral aneurysm fluid-structure interaction upstream parent artery wall tension hemodynamics

Cell cycle-dependent gene networks relevant to cancer

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Progress in Natural Science:Materials International 2008年第8期18卷 945-952页

作者： Yun Xiao a,1, Xia Lia,b,*,1, Yueying Yang a, Yadong Wangc, Shaoqi Rao a,b a College of Bioinformatics Science and Technology, and Bio-pharmaceutical Key Laboratory of Heilongjiang Province and State, Harbin medical university, Harbin 15.086, china b biomedical {4. {5. of capital medical university, beijing 10004. china c Department of Computer Science, Harbin {5. of Technology, Harbin 15.080, china College of Bioinformatics Science and Technology and Bio-pharmaceutical Key Laboratory of Heilongjiang Province and State Harbin Medical University Harbin 150086 China biomedical engineering institute of capital {4. {5. Beijing 10004 China Department of Computer Science Harbin Institute of Technology Harbin 150080 China

The analysis of sophisticated interplays between cell cycle-dependent genes in a disease condition is one of the largely unexplored areas in modern tumor biology research. Many cell cycle-dependent genes are either oncogenes or suppressor genes, or are closely associated with the transition of a cell cycle. However, it is unclear how the complicated relationships between these cell cycle-dependent genes are, especially in cancers. Here, we sought to identify significant expression relationships between cell cycle-dependent genes by analyzing a HeLa microarray dataset using a local alignment algorithm and constructed a gene transcriptional network specific to the cancer by assembling these newly identified gene-gene relationships. We further characterized this global network by partitioning the whole network into several cell cycle phase-specific sub-networks. All generated networks exhibited the power-law node-degree distribution, and the average clustering coefficients of these networks were remarkably higher than those of pure scale-free networks, indicating a property of hierarchical modularity. Based on the known protein-protein interactions and Gene Ontology annotation data, the proteins encoded by cell cycle-dependent interacting genes tended to share the same biological functions or to be involved in the same biological processes, rather than interacting by physical means. Finally, we identified the hub genes related to cancer based on the topological importance that maintain the basic structure of cell cycle-dependent gene networks.

关键词： Cell cycle Microarray HeLa cell Gene network

Identifying drug-target proteins based on network features

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Science china(Life Sciences) 2009年第4期52卷 398-404页

作者： ZHU MingZhu1, GAO Lei1, LI Xia1,2 & LIU ZhiCheng1 1 School of biomedical engineering, capital medical {4., {5. 100069, china 2 College of Bioinformatics Science and Technology, Harbin medical {4., Harbin 15.081, china 1. School of biomedical engineering Capital Medical University Beijing 100069 China 2. College of Bioinformatics Science and Technology Harbin Medical University Harbin 150081 China

Proteins rarely function in isolation inside and outside cells, but operate as part of a highly intercon- nected cellular network called the interaction network. Therefore, the analysis of the properties of drug-target proteins in the biological network is especially helpful for understanding the mechanism of drug action in terms of informatics. At present, no detailed characterization and description of the topological features of drug-target proteins have been available in the human protein-protein interac- tion network. In this work, by mapping the drug-targets in DrugBank onto the interaction network of human proteins, five topological indices of drug-targets were analyzed and compared with those of the whole protein interactome set and the non-drug-target set. The experimental results showed that drug-target proteins have higher connectivity and quicker communication with each other in the PPI network. Based on these features, all proteins in the interaction network were ranked. The results showed that, of the top 100 proteins, 4. are covered by DrugBank; of the remaining 5. proteins, 9 are drug-target proteins covered by the TTD, Matador and other databases, while others have been dem- onstrated to be drug-target proteins in the literature.

关键词： drug-target protein-protein interaction topological features